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 id,doi,title,authorString,authorAffiliations,journalTitle,pubYear,abstract
 30950797,https://doi.org/10.2196/12286,Applications of Machine Learning in Real-Life Digital Health Interventions: Review of the Literature.,"Triantafyllidis AK, Tsanas A.","Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece.; Usher Institute of Population Health Sciences and Informatics, Medical School, University of Edinburgh, Edinburgh, United Kingdom.",Journal of medical Internet research,2019,"BACKGROUND:Machine learning has attracted considerable research interest toward developing smart digital health interventions. These interventions have the potential to revolutionize health care and lead to substantial outcomes for patients and medical professionals. OBJECTIVE:Our objective was to review the literature on applications of machine learning in real-life digital health interventions, aiming to improve the understanding of researchers, clinicians, engineers, and policy makers in developing robust and impactful data-driven interventions in the health care domain. METHODS:We searched the PubMed and Scopus bibliographic databases with terms related to machine learning, to identify real-life studies of digital health interventions incorporating machine learning algorithms. We grouped those interventions according to their target (ie, target condition), study design, number of enrolled participants, follow-up duration, primary outcome and whether this had been statistically significant, machine learning algorithms used in the intervention, and outcome of the algorithms (eg, prediction). RESULTS:Our literature search identified 8 interventions incorporating machine learning in a real-life research setting, of which 3 (37%) were evaluated in a randomized controlled trial and 5 (63%) in a pilot or experimental single-group study. The interventions targeted depression prediction and management, speech recognition for people with speech disabilities, self-efficacy for weight loss, detection of changes in biopsychosocial condition of patients with multiple morbidity, stress management, treatment of phantom limb pain, smoking cessation, and personalized nutrition based on glycemic response. The average number of enrolled participants in the studies was 71 (range 8-214), and the average follow-up study duration was 69 days (range 3-180). Of the 8 interventions, 6 (75%) showed statistical significance (at the P=.05 level) in health outcomes. CONCLUSIONS:This review found that digital health interventions incorporating machine learning algorithms in real-life studies can be useful and effective. Given the low number of studies identified in this review and that they did not follow a rigorous machine learning evaluation methodology, we urge the research community to conduct further studies in intervention settings following evaluation principles and demonstrating the potential of machine learning in clinical practice."
-30984881,https://doi.org/10.12688/wellcomeopenres.15151.1,Causes of death among homeless people: a population-based cross-sectional study of linked hospitalisation and mortality data in England.,"Aldridge RW, Menezes D, Lewer D, Cornes M, Evans H, Blackburn RM, Byng R, Clark M, Denaxas S, Fuller J, Hewett N, Kilmister A, Luchenski S, Manthorpe J, McKee M, Neale J, Story A, Tinelli M, Whiteford M, Wurie F, Hayward A.","Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Community and Primary Care Research Group, University of Plymouth, Plymouth, Devon, PL6 8BX, UK.; Personal Social Services Research Unit, London School of Economics, London, WC2A 2AE, UK.; Institute of Health Informatics, University College London, London, NW1 2DA, UK.; NIHR Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Pathway Charity, Pathway Charity, London, NW1 2PG, UK.; Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Collaborative Centre for Inclusion Health, Institute of Epidemiology & Health Care, University College London, London, NW1 2DA, UK.; Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Department of Health Services Research & Policy, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.; National Addiction Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE1 1UL, UK.; Collaborative Centre for Inclusion Health, Institute of Epidemiology & Health Care, University College London, London, NW1 2DA, UK.; Personal Social Services Research Unit, London School of Economics, London, WC2A 2AE, UK.; Health Services Research, University of Liverpool, Liverpool, L69 3BX, UK.; Public Health England, London, NW9 5EQ, UK.; Collaborative Centre for Inclusion Health, Institute of Epidemiology & Health Care, University College London, London, NW1 2DA, UK.",Wellcome open research,2019,"Background: Homelessness has increased by 165% since 2010 in England, with evidence from many settings that those affected experience high levels of mortality. In this paper we examine the contribution of different causes of death to overall mortality in homeless people recently admitted to hospitals in England with specialist integrated homeless health and care (SIHHC) schemes.  Methods: We undertook an analysis of linked hospital admission records and mortality data for people attending any one of 17 SIHHC schemes between 1st November 2013 and 30th November 2016. Our primary outcome was death, which we analysed in subgroups of 10th version international classification of disease (ICD-10) specific deaths; and deaths from amenable causes. We compared our results to a sample of people living in areas of high social deprivation (IMD5 group). Results: We collected data on 3,882 individual homeless hospital admissions that were linked to 600 deaths. The median age of death was 51.6 years (interquartile range 42.7-60.2) for SIHHC and 71.5 for the IMD5 (60.67-79.0).  The top three underlying causes of death by ICD-10 chapter in the SIHHC group were external causes of death (21.7%; 130/600), cancer (19.0%; 114/600) and digestive disease (19.0%; 114/600).  The percentage of deaths due to an amenable cause after age and sex weighting was 30.2% in the homeless SIHHC group (181/600) compared to 23.0% in the IMD5 group (578/2,512). Conclusion: Nearly one in three homeless deaths were due to causes amenable to timely and effective health care. The high burden of amenable deaths highlights the extreme health harms of homelessness and the need for greater emphasis on prevention of homelessness and early healthcare interventions."
 31000744,https://doi.org/10.1038/s41598-019-42036-w,"Measuring social, environmental and health inequalities using deep learning and street imagery.","Suel E, Polak JW, Bennett JE, Ezzati M.","School of Public Health, Imperial College London, London, UK. esra.suel@imperial.ac.uk.; Urban Systems Laboratory, Imperial College London, London, SW7 2AZ, United Kingdom.; School of Public Health, Imperial College London, London, UK.; School of Public Health, Imperial College London, London, UK.",Scientific reports,2019,"Cities are home to an increasing majority of the world's population. Currently, it is difficult to track social, economic, environmental and health outcomes in cities with high spatial and temporal resolution, needed to evaluate policies regarding urban inequalities. We applied a deep learning approach to street images for measuring spatial distributions of income, education, unemployment, housing, living environment, health and crime. Our model predicts different outcomes directly from raw images without extracting intermediate user-defined features. To evaluate the performance of the approach, we first trained neural networks on a subset of images from London using ground truth data at high spatial resolution from official statistics. We then compared how trained networks separated the best-off from worst-off deciles for different outcomes in images not used in training. The best performance was achieved for quality of the living environment and mean income. Allocation was least successful for crime and self-reported health (but not objectively measured health). We also evaluated how networks trained in London predict outcomes three other major cities in the UK: Birmingham, Manchester, and Leeds. The transferability analysis showed that networks trained in London, fine-tuned with only 1% of images in other cities, achieved performances similar to ones from trained on data from target cities themselves. Our findings demonstrate that street imagery has the potential complement traditional survey-based and administrative data sources for high-resolution urban surveillance to measure inequalities and monitor the impacts of policies that aim to address them."
+30984881,https://doi.org/10.12688/wellcomeopenres.15151.1,Causes of death among homeless people: a population-based cross-sectional study of linked hospitalisation and mortality data in England.,"Aldridge RW, Menezes D, Lewer D, Cornes M, Evans H, Blackburn RM, Byng R, Clark M, Denaxas S, Fuller J, Hewett N, Kilmister A, Luchenski S, Manthorpe J, McKee M, Neale J, Story A, Tinelli M, Whiteford M, Wurie F, Hayward A.","Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Community and Primary Care Research Group, University of Plymouth, Plymouth, Devon, PL6 8BX, UK.; Personal Social Services Research Unit, London School of Economics, London, WC2A 2AE, UK.; Institute of Health Informatics, University College London, London, NW1 2DA, UK.; NIHR Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Pathway Charity, Pathway Charity, London, NW1 2PG, UK.; Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Collaborative Centre for Inclusion Health, Institute of Epidemiology & Health Care, University College London, London, NW1 2DA, UK.; Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Department of Health Services Research & Policy, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.; National Addiction Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE1 1UL, UK.; Collaborative Centre for Inclusion Health, Institute of Epidemiology & Health Care, University College London, London, NW1 2DA, UK.; Personal Social Services Research Unit, London School of Economics, London, WC2A 2AE, UK.; Health Services Research, University of Liverpool, Liverpool, L69 3BX, UK.; Public Health England, London, NW9 5EQ, UK.; Collaborative Centre for Inclusion Health, Institute of Epidemiology & Health Care, University College London, London, NW1 2DA, UK.",Wellcome open research,2019,"Background: Homelessness has increased by 165% since 2010 in England, with evidence from many settings that those affected experience high levels of mortality. In this paper we examine the contribution of different causes of death to overall mortality in homeless people recently admitted to hospitals in England with specialist integrated homeless health and care (SIHHC) schemes.  Methods: We undertook an analysis of linked hospital admission records and mortality data for people attending any one of 17 SIHHC schemes between 1st November 2013 and 30th November 2016. Our primary outcome was death, which we analysed in subgroups of 10th version international classification of disease (ICD-10) specific deaths; and deaths from amenable causes. We compared our results to a sample of people living in areas of high social deprivation (IMD5 group). Results: We collected data on 3,882 individual homeless hospital admissions that were linked to 600 deaths. The median age of death was 51.6 years (interquartile range 42.7-60.2) for SIHHC and 71.5 for the IMD5 (60.67-79.0).  The top three underlying causes of death by ICD-10 chapter in the SIHHC group were external causes of death (21.7%; 130/600), cancer (19.0%; 114/600) and digestive disease (19.0%; 114/600).  The percentage of deaths due to an amenable cause after age and sex weighting was 30.2% in the homeless SIHHC group (181/600) compared to 23.0% in the IMD5 group (578/2,512). Conclusion: Nearly one in three homeless deaths were due to causes amenable to timely and effective health care. The high burden of amenable deaths highlights the extreme health harms of homelessness and the need for greater emphasis on prevention of homelessness and early healthcare interventions."
+31104603,https://doi.org/10.1098/rstb.2018.0276,Outbreak analytics: a developing data science for informing the response to emerging pathogens.,"Polonsky JA, Baidjoe A, Kamvar ZN, Cori A, Durski K, Edmunds WJ, Eggo RM, Funk S, Kaiser L, Keating P, de Waroux OLP, Marks M, Moraga P, Morgan O, Nouvellet P, Ratnayake R, Roberts CH, Whitworth J, Jombart T.","1 Department of Health Emergency Information and Risk Assessment, World Health Organization , Avenue Appia 20, 1211 Geneva , Switzerland.; 4 Department of Infectious Disease Epidemiology, School of Public Health, MRC Centre for Global Infectious Disease Analysis, Imperial College London , Medical School Building, St Mary's Campus, Norfolk Place London W2 1PG , UK.; 4 Department of Infectious Disease Epidemiology, School of Public Health, MRC Centre for Global Infectious Disease Analysis, Imperial College London , Medical School Building, St Mary's Campus, Norfolk Place London W2 1PG , UK.; 4 Department of Infectious Disease Epidemiology, School of Public Health, MRC Centre for Global Infectious Disease Analysis, Imperial College London , Medical School Building, St Mary's Campus, Norfolk Place London W2 1PG , UK.; 2 Department of Infectious Hazard Management, World Health Organization , Avenue Appia 20, 1211 Geneva , Switzerland.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 3 Faculty of Medicine, University of Geneva , 1 rue Michel-Servet, 1211 Geneva , Switzerland.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 7 Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 10 Centre for Health Informatics, Computing and Statistics (CHICAS), Lancaster Medical School, Lancaster University , Lancaster LA1 4YW , UK.; 1 Department of Health Emergency Information and Risk Assessment, World Health Organization , Avenue Appia 20, 1211 Geneva , Switzerland.; 4 Department of Infectious Disease Epidemiology, School of Public Health, MRC Centre for Global Infectious Disease Analysis, Imperial College London , Medical School Building, St Mary's Campus, Norfolk Place London W2 1PG , UK.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 7 Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 4 Department of Infectious Disease Epidemiology, School of Public Health, MRC Centre for Global Infectious Disease Analysis, Imperial College London , Medical School Building, St Mary's Campus, Norfolk Place London W2 1PG , UK.","Philosophical transactions of the Royal Society of London. Series B, Biological sciences",2019,"Despite continued efforts to improve health systems worldwide, emerging pathogen epidemics remain a major public health concern. Effective response to such outbreaks relies on timely intervention, ideally informed by all available sources of data. The collection, visualization and analysis of outbreak data are becoming increasingly complex, owing to the diversity in types of data, questions and available methods to address them. Recent advances have led to the rise of outbreak analytics, an emerging data science focused on the technological and methodological aspects of the outbreak data pipeline, from collection to analysis, modelling and reporting to inform outbreak response. In this article, we assess the current state of the field. After laying out the context of outbreak response, we critically review the most common analytics components, their inter-dependencies, data requirements and the type of information they can provide to inform operations in real time. We discuss some challenges and opportunities and conclude on the potential role of outbreak analytics for improving our understanding of, and response to outbreaks of emerging pathogens. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'."
 30423068,https://doi.org/10.1093/bioinformatics/bty605,Ontology-based validation and identification of regulatory phenotypes.,"Kulmanov M, Schofield PN, Gkoutos GV, Hoehndorf R.","Computer, Electrical and Mathematical Sciences and Engineering Division, Computational Bioscience Research Centre, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.; Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.; College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, UK.; Computer, Electrical and Mathematical Sciences and Engineering Division, Computational Bioscience Research Centre, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.","Bioinformatics (Oxford, England)",2018,"Motivation:Function annotations of gene products, and phenotype annotations of genotypes, provide valuable information about molecular mechanisms that can be utilized by computational methods to identify functional and phenotypic relatedness, improve our understanding of disease and pathobiology, and lead to discovery of drug targets. Identifying functions and phenotypes commonly requires experiments which are time-consuming and expensive to carry out; creating the annotations additionally requires a curator to make an assertion based on reported evidence. Support to validate the mutual consistency of functional and phenotype annotations as well as a computational method to predict phenotypes from function annotations, would greatly improve the utility of function annotations. Results:We developed a novel ontology-based method to validate the mutual consistency of function and phenotype annotations. We apply our method to mouse and human annotations, and identify several inconsistencies that can be resolved to improve overall annotation quality. We also apply our method to the rule-based prediction of regulatory phenotypes from functions and demonstrate that we can predict these phenotypes with Fmax of up to 0.647. Availability and implementation:https://github.com/bio-ontology-research-group/phenogocon."
 29716529,https://doi.org/10.1186/s12883-018-1058-8,Severe localised granulomatosis with polyangiitis (Wegener's granulomatosis) manifesting with extensive cranial nerve palsies and cranial diabetes insipidus: a case report and literature review.,"Peters JE, Gupta V, Saeed IT, Offiah C, Jawad ASM.","Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, Worts Causeway, University of Cambridge, Cambridge, CB1 8RN, UK. jp549@cam.ac.uk.; Department of Rheumatology, The Royal London and Mile End Hospitals, Barts Health NHS Trust, Bancroft Road, London, E1 4DG, UK.; Department of Histopathology, Queen's Hospital, Rom Valley Road, Romford, RM7 0AG, UK.; Department of Radiology, The Royal London Hospital, Barts Health NHS Trust, Whitechapel Road, London, E1 1BB, UK.; Department of Rheumatology, The Royal London and Mile End Hospitals, Barts Health NHS Trust, Bancroft Road, London, E1 4DG, UK.",BMC neurology,2018,"BACKGROUND:Granulomatosis with polyangiitis (GPA, formerly Wegener's granulomatosis) is a multisystem vasculitis of small- to medium-sized blood vessels. Cranial involvement can result in cranial nerve palsies and, rarely, pituitary infiltration. CASE PRESENTATION:We describe the case of a 32 year-old woman with limited but severe GPA manifesting as progressive cranial nerve palsies and pituitary dysfunction. Our patient initially presented with localised ENT involvement, but despite treatment with methotrexate, she deteriorated. Granulomatous inflammatory tissue around the skull base resulted in cavernous sinus syndrome, facial nerve palsy, palsies of cranial nerves IX-XII (Collet-Sicard syndrome), and the rare complication of cranial diabetes insipidus due to pituitary infiltration. The glossopharyngeal, vagus and accessory nerve palsies resulted in severe dysphagia and she required nasogastric tube feeding. Her neurological deficits substantially improved with treatment including high dose corticosteroid, cyclophosphamide and rituximab. CONCLUSIONS:This case emphasises that serious morbidity can arise from localised cranial Wegener's granulomatosis in the absence of systemic disease. In such cases intensive induction immunosuppression is required. Analysis of previously reported cases of pituitary involvement in GPA reveals that this rare complication predominantly affects female patients."
 30381314,https://doi.org/10.1136/bmjopen-2018-026290,Study protocol for investigating the impact of community home modification services on hospital utilisation for fall injuries: a controlled longitudinal study using data linkage.,"Hollinghurst J, Akbari A, Fry R, Watkins A, Berridge D, Clegg A, Hillcoat-Nalletamby S, Williams N, Lyons R, Mizen A, Walters A, Johnson R, Rodgers S.","Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; University of Leeds (Bradford Teaching Hospital), Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK.; College of Human and Health Sciences, Swansea University, Swansea, UK.; Care & Repair Cymru, Cardiff, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.",BMJ open,2018,"INTRODUCTION:This study will evaluate the effectiveness of home adaptations, both in preventing hospital admissions due to falls for older people, and improving timely discharge. Results will provide evidence for services at the interface between health and social care, informing policies seeking to promote healthy ageing through prudent healthcare and fall prevention. METHODS AND ANALYSIS:All individuals living in Wales, UK, aged 60 years and over, will be included in the study using anonymised linked data from the Secure Anonymised Information Linkage Databank. We will use a national database of home modifications implemented by the charity organisation Care & Repair Cymru (C&R) from 2009 to 2017 to define an intervention cohort. We will use the electronic Frailty Index to assign individual levels of frailty (fit, mild, moderate or severe) and use these to create a comparator group (non-C&R) of people who have not received a C&R intervention. Coprimary outcomes will be quarterly numbers of emergency hospital admissions attributed to falls at home, and the associated length of stay. Secondary outcomes include the time in moving to a care home following a fall, and the indicative financial costs of care for individuals who had a fall. We will use appropriate multilevel generalised linear models to analyse the number of hospital admissions related to falls. We will use Cox proportional hazard models to compare the length of stay for fall-related hospital admissions and the time in moving to a care home between the C&R and non-C&R cohorts. We will assess the impact per frailty group, correct for population migration and adjust for confounding variables. Indicative costs will be calculated using financial codes for individual-level hospital stays. Results will provide evidence for services at the interface between health and social care, informing policies seeking to promote healthy ageing through prudent healthcare and prevention. ETHICS AND DISSEMINATION:Information governance requirements for the use of record-linked data have been approved and only anonymised data will be used in our analysis. Our results will be submitted for publication in peer-reviewed journals. We will also work with lay members and the knowledge transfer team at Swansea University to create communication and dissemination materials on key findings."
+30727941,https://doi.org/10.1186/s12859-019-2633-8,DeepPVP: phenotype-based prioritization of causative variants using deep learning.,"Boudellioua I, Kulmanov M, Schofield PN, Gkoutos GV, Hoehndorf R.","Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia.; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia.; Department of Physiology, Development & Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK.; College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, B15 2TT, UK.; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia. robert.hoehndorf@kaust.edu.sa.",BMC bioinformatics,2019,"BACKGROUND:Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In these methods, pathogenicity prediction is combined with a semantic similarity measure to prioritize not only variants that are likely to be dysfunctional but those that are likely involved in the pathogenesis of a patient's phenotype. RESULTS:We have developed DeepPVP, a variant prioritization method that combined automated inference with deep neural networks to identify the likely causative variants in whole exome or whole genome sequence data. We demonstrate that DeepPVP performs significantly better than existing methods, including phenotype-based methods that use similar features. DeepPVP is freely available at https://github.com/bio-ontology-research-group/phenomenet-vp . CONCLUSIONS:DeepPVP further improves on existing variant prioritization methods both in terms of speed as well as accuracy."
 30532623,https://doi.org/10.3897/BDJ.6.e29232,"Modifier Ontologies for frequency, certainty, degree, and coverage phenotype modifier.","Endara L, Thessen AE, Cole HA, Walls R, Gkoutos G, Cao Y, Chong SS, Cui H.","University of Florida, Gainesville, United States of America University of Florida Gainesville United States of America.; The Ronin Institute for Independent Scholarship, Monclair, NJ, United States of America The Ronin Institute for Independent Scholarship Monclair, NJ United States of America.; Science and Technology Branch, Agriculture and Agri-Food Canada, Government of Canada, Ottawa, Canada Science and Technology Branch, Agriculture and Agri-Food Canada, Government of Canada Ottawa Canada.; CyVerse, Tucson, United States of America CyVerse Tucson United States of America.; College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham Birmingham United Kingdom.; Center for Studies of Information Resources, Wuhan Universtity, Wuhan, China Center for Studies of Information Resources, Wuhan Universtity Wuhan China.; National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, Santa Barbara, United States of America National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara Santa Barbara United States of America.; University of Arizona, Tucson, United States of America University of Arizona Tucson United States of America.",Biodiversity data journal,2018,"Background: When phenotypic characters are described in the literature, they may be constrained or clarified with additional information such as the location or degree of expression, these terms are called ""modifiers"". With effort underway to convert narrative character descriptions to computable data, ontologies for such modifiers are needed. Such ontologies can also be used to guide term usage in future publications. Spatial and method modifiers are the subjects of ontologies that already have been developed or are under development. In this work, frequency (e.g., rarely, usually), certainty (e.g., probably, definitely), degree (e.g., slightly, extremely), and coverage modifiers (e.g., sparsely, entirely) are collected, reviewed, and used to create two modifier ontologies with different design considerations. The basic goal is to express the sequential relationships within a type of modifiers, for example, usually is more frequent than rarely, in order to allow data annotated with ontology terms to be classified accordingly. Method: Two designs are proposed for the ontology, both using the list pattern: a closed ordered list (i.e., five-bin design) and an open ordered list design. The five-bin design puts the modifier terms into a set of 5 fixed bins with interval object properties, for example, one_level_more/less_frequently_than, where new terms can only be added as synonyms to existing classes. The open list approach starts with 5 bins, but supports the extensibility of the list via ordinal properties, for example, more/less_frequently_than, allowing new terms to be inserted as a new class anywhere in the list. The consequences of the different design decisions are discussed in the paper. CharaParser was used to extract modifiers from plant, ant, and other taxonomic descriptions. After a manual screening, 130 modifier words were selected as the candidate terms for the modifier ontologies. Four curators/experts (three biologists and one information scientist specialized in biosemantics) reviewed and categorized the terms into 20 bins using the Ontology Term Organizer (OTO) (http://biosemantics.arizona.edu/OTO). Inter-curator variations were reviewed and expressed in the final ontologies. Results: Frequency, certainty, degree, and coverage terms with complete agreement among all curators were used as class labels or exact synonyms. Terms with different interpretations were either excluded or included using ""broader synonym"" or ""not recommended"" annotation properties. These annotations explicitly allow for the user to be aware of the semantic ambiguity associated with the terms and whether they should be used with caution or avoided. Expert categorization results showed that 16 out of 20 bins contained terms with full agreements, suggesting differentiating the modifiers into 5 levels/bins balances the need to differentiate modifiers and the need for the ontology to reflect user consensus. Two ontologies, developed using the Protege ontology editor, are made available as OWL files and can be downloaded from https://github.com/biosemantics/ontologies. Contribution: We built the first two modifier ontologies following a consensus-based approach with terms commonly used in taxonomic literature. The five-bin ontology has been used in the Explorer of Taxon Concepts web toolkit to compute the similarity between characters extracted from literature to facilitate taxon concepts alignments. The two ontologies will also be used in an ontology-informed authoring tool for taxonomists to facilitate consistency in modifier term usage."
 30279426,https://doi.org/10.1038/s41598-018-32876-3,OligoPVP: Phenotype-driven analysis of individual genomic information to prioritize oligogenic disease variants.,"Boudellioua I, Kulmanov M, Schofield PN, Gkoutos GV, Hoehndorf R.","Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.; Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.; Department of Physiology, Development & Neuroscience, University of Cambridge, Cambridge, UK.; College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, B15 2TT, Birmingham, United Kingdom.; Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. robert.hoehndorf@kaust.edu.sa.",Scientific reports,2018,"An increasing number of disorders have been identified for which two or more distinct alleles in two or more genes are required to either cause the disease or to significantly modify its onset, severity or phenotype. It is difficult to discover such interactions using existing approaches. The purpose of our work is to develop and evaluate a system that can identify combinations of alleles underlying digenic and oligogenic diseases in individual whole exome or whole genome sequences. Information that links patient phenotypes to databases of gene-phenotype associations observed in clinical or non-human model organism research can provide useful information and improve variant prioritization for genetic diseases. Additional background knowledge about interactions between genes can be utilized to identify sets of variants in different genes in the same individual which may then contribute to the overall disease phenotype. We have developed OligoPVP, an algorithm that can be used to prioritize causative combinations of variants in digenic and oligogenic diseases, using whole exome or whole genome sequences together with patient phenotypes as input. We demonstrate that OligoPVP has significantly improved performance when compared to state of the art pathogenicity detection methods in the case of digenic diseases. Our results show that OligoPVP can efficiently prioritize sets of variants in digenic diseases using a phenotype-driven approach and identify etiologically important variants in whole genomes. OligoPVP naturally extends to oligogenic disease involving interactions between variants in two or more genes. It can be applied to the identification of multiple interacting candidate variants contributing to phenotype, where the action of modifier genes is suspected from pedigree analysis or failure of traditional causative variant identification."
 30240446,https://doi.org/10.1371/journal.pone.0203896,Polygenic risk scores for major depressive disorder and neuroticism as predictors of antidepressant response: Meta-analysis of three treatment cohorts.,"Ward J, Graham N, Strawbridge RJ, Ferguson A, Jenkins G, Chen W, Hodgson K, Frye M, Weinshilboum R, Uher R, Lewis CM, Biernacka J, Smith DJ.","Institute of Health And Wellbeing, University of Glasgow, Glasgow, Scotland.; Institute of Health And Wellbeing, University of Glasgow, Glasgow, Scotland.; Institute of Health And Wellbeing, University of Glasgow, Glasgow, Scotland.; Institute of Health And Wellbeing, University of Glasgow, Glasgow, Scotland.; Mayo Clinic, Rochester, MN, United States of America.; St. Jude Children's Research Hospital, Memphis, TN, United States of America.; King's College London, London, England.; Mayo Clinic, Rochester, MN, United States of America.; Mayo Clinic, Rochester, MN, United States of America.; Dalhousie University, Halifax, Canada.; King's College London, London, England.; Mayo Clinic, Rochester, MN, United States of America.; Institute of Health And Wellbeing, University of Glasgow, Glasgow, Scotland.",PloS one,2018,"There are currently no reliable approaches for correctly identifying which patients with major depressive disorder (MDD) will respond well to antidepressant therapy. However, recent genetic advances suggest that Polygenic Risk Scores (PRS) could allow MDD patients to be stratified for antidepressant response. We used PRS for MDD and PRS for neuroticism as putative predictors of antidepressant response within three treatment cohorts: The Genome-based Therapeutic Drugs for Depression (GENDEP) cohort, and 2 sub-cohorts from the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomics Study PRGN-AMPS (total patient number = 760). Results across cohorts were combined via meta-analysis within a random effects model. Overall, PRS for MDD and neuroticism did not significantly predict antidepressant response but there was a consistent direction of effect, whereby greater genetic loading for both MDD (best MDD result, p < 5*10-5 MDD-PRS at 4 weeks, β = -0.019, S.E = 0.008, p = 0.01) and neuroticism (best neuroticism result, p < 0.1 neuroticism-PRS at 8 weeks, β = -0.017, S.E = 0.008, p = 0.03) were associated with less favourable response. We conclude that the PRS approach may offer some promise for treatment stratification in MDD and should now be assessed within larger clinical cohorts."
-30727941,https://doi.org/10.1186/s12859-019-2633-8,DeepPVP: phenotype-based prioritization of causative variants using deep learning.,"Boudellioua I, Kulmanov M, Schofield PN, Gkoutos GV, Hoehndorf R.","Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia.; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia.; Department of Physiology, Development & Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK.; College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, B15 2TT, UK.; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia. robert.hoehndorf@kaust.edu.sa.",BMC bioinformatics,2019,"BACKGROUND:Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In these methods, pathogenicity prediction is combined with a semantic similarity measure to prioritize not only variants that are likely to be dysfunctional but those that are likely involved in the pathogenesis of a patient's phenotype. RESULTS:We have developed DeepPVP, a variant prioritization method that combined automated inference with deep neural networks to identify the likely causative variants in whole exome or whole genome sequence data. We demonstrate that DeepPVP performs significantly better than existing methods, including phenotype-based methods that use similar features. DeepPVP is freely available at https://github.com/bio-ontology-research-group/phenomenet-vp . CONCLUSIONS:DeepPVP further improves on existing variant prioritization methods both in terms of speed as well as accuracy."
 29457906,https://doi.org/10.1021/acs.jproteome.7b00879,Optimized Phenotypic Biomarker Discovery and Confounder Elimination via Covariate-Adjusted Projection to Latent Structures from Metabolic Spectroscopy Data.,"Posma JM, Garcia-Perez I, Ebbels TMD, Lindon JC, Stamler J, Elliott P, Holmes E, Nicholson JK.","Investigative Medicine, Department of Medicine, Faculty of Medicine , Imperial College London , W12 0NN London , United Kingdom.; Department of Preventive Medicine, Feinberg School of Medicine , Northwestern University , Chicago , Illinois 60611 , United States.",Journal of proteome research,2018,"Metabolism is altered by genetics, diet, disease status, environment, and many other factors. Modeling either one of these is often done without considering the effects of the other covariates. Attributing differences in metabolic profile to one of these factors needs to be done while controlling for the metabolic influence of the rest. We describe here a data analysis framework and novel confounder-adjustment algorithm for multivariate analysis of metabolic profiling data. Using simulated data, we show that similar numbers of true associations and significantly less false positives are found compared to other commonly used methods. Covariate-adjusted projections to latent structures (CA-PLS) are exemplified here using a large-scale metabolic phenotyping study of two Chinese populations at different risks for cardiovascular disease. Using CA-PLS, we find that some previously reported differences are actually associated with external factors and discover a number of previously unreported biomarkers linked to different metabolic pathways. CA-PLS can be applied to any multivariate data where confounding may be an issue and the confounder-adjustment procedure is translatable to other multivariate regression techniques."
-31101093,https://doi.org/10.1186/s12889-019-6888-9,Educational and health outcomes of children and adolescents receiving antiepileptic medication: Scotland-wide record linkage study of 766 244 schoolchildren.,"Fleming M, Fitton CA, Steiner MFC, McLay JS, Clark D, King A, Mackay DF, Pell JP.","Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK. michael.fleming@glasgow.ac.uk.; Department of Child Health, University of Aberdeen, Aberdeen, AB25 2ZG, UK.; Department of Child Health, University of Aberdeen, Aberdeen, AB25 2ZG, UK.; Department of Child Health, University of Aberdeen, Aberdeen, AB25 2ZG, UK.; Information Services Division, Edinburgh, EH12 9EB, UK.; ScotXed, Scottish Government, Edinburgh, EH6 6QQ, UK.; Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK.; Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK.",BMC public health,2019,"BACKGROUND:Childhood epilepsy can adversely affect education and employment in addition to health. Previous studies are small or highly selective producing conflicting results. This retrospective cohort study aims to compare educational and health outcomes of children receiving antiepileptic medication versus peers. METHODS:Record linkage of Scotland-wide databases covering dispensed prescriptions, acute and psychiatric hospitalisations, maternity records, deaths, annual pupil census, school absences/exclusions, special educational needs, school examinations, and (un)employment provided data on 766,244 children attending Scottish schools between 2009 and 2013. Outcomes were adjusted for sociodemographic and maternity confounders and comorbid conditions. RESULTS:Compared with peers, children on antiepileptic medication were more likely to experience school absence (Incidence Rate Ratio [IRR] 1.43, 95% CI: 1.38, 1.48), special educational needs (Odds ratio [OR] 9.60, 95% CI: 9.02, 10.23), achieve the lowest level of attainment (OR 3.43, 95% CI: 2.74, 4.29) be unemployed (OR 1.82, 95% CI: 1.60, 2.07), be admitted to hospital (Hazard Ratio [HR] 3.56, 95% CI: 3.42, 3.70), and die (HR 22.02, 95% CI: 17.00, 28.53). Absenteeism partly explained poorer attainment and higher unemployment. Girls and younger children on antiepileptic medication had higher risk of poor outcomes. CONCLUSIONS:Children on antiepileptic medication fare worse than peers across educational and health outcomes. In order to reduce school absenteeism and mitigate its effects, children with epilepsy should receive integrated care from a multidisciplinary team that spans education and healthcare."
 30181555,https://doi.org/10.1038/s41398-018-0236-1,"Genetics of self-reported risk-taking behaviour, trans-ethnic consistency and relevance to brain gene expression.","Strawbridge RJ, Ward J, Lyall LM, Tunbridge EM, Cullen B, Graham N, Ferguson A, Johnston KJA, Lyall DM, Mackay D, Cavanagh J, Howard DM, Adams MJ, Deary I, Escott-Price V, O'Donovan M, McIntosh AM, Bailey MES, Pell JP, Harrison PJ, Smith DJ.","Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK. rona.strawbridge@glasgow.ac.uk.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Department of Psychiatry, University of Oxford, Oxford, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK.; Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK.; Department of Psychology, University of Edinburgh, Edinburgh, EH8 9YL, UK.; MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.; MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.; Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK.; School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Department of Psychiatry, University of Oxford, Oxford, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.",Translational psychiatry,2018,"Risk-taking behaviour is an important component of several psychiatric disorders, including attention-deficit hyperactivity disorder, schizophrenia and bipolar disorder. Previously, two genetic loci have been associated with self-reported risk taking and significant genetic overlap with psychiatric disorders was identified within a subsample of UK Biobank. Using the white British participants of the full UK Biobank cohort (n = 83,677 risk takers versus 244,662 controls) for our primary analysis, we conducted a genome-wide association study of self-reported risk-taking behaviour. In secondary analyses, we assessed sex-specific effects, trans-ethnic heterogeneity and genetic overlap with psychiatric traits. We also investigated the impact of risk-taking-associated SNPs on both gene expression and structural brain imaging. We identified 10 independent loci for risk-taking behaviour, of which eight were novel and two replicated previous findings. In addition, we found two further sex-specific risk-taking loci. There were strong positive genetic correlations between risk-taking and attention-deficit hyperactivity disorder, bipolar disorder and schizophrenia. Index genetic variants demonstrated effects generally consistent with the discovery analysis in individuals of non-British White, South Asian, African-Caribbean or mixed ethnicity. Polygenic risk scores comprising alleles associated with increased risk taking were associated with lower white matter integrity. Genotype-specific expression pattern analyses highlighted DPYSL5, CGREF1 and C15orf59 as plausible candidate genes. Overall, our findings substantially advance our understanding of the biology of risk-taking behaviour, including the possibility of sex-specific contributions, and reveal consistency across ethnicities. We further highlight several putative novel candidate genes, which may mediate these genetic effects."
 30745170,https://doi.org/10.1016/j.ebiom.2019.02.005,"Identification of novel genome-wide associations for suicidality in UK Biobank, genetic correlation with psychiatric disorders and polygenic association with completed suicide.","Strawbridge RJ, Ward J, Ferguson A, Graham N, Shaw RJ, Cullen B, Pearsall R, Lyall LM, Johnston KJA, Niedzwiedz CL, Pell JP, Mackay D, Martin JL, Lyall DM, Bailey MES, Smith DJ.","Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK; Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK; Division of Psychiatry, College of Medicine, University of Edinburgh, UK; School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK. Electronic address: Daniel.Smith@glasgow.ac.uk.",EBioMedicine,2019,"BACKGROUND:Suicide is a major issue for global public health. Suicidality describes a broad spectrum of thoughts and behaviours, some of which are common in the general population. Although suicide results from a complex interaction of multiple social and psychological factors, predisposition to suicidality is at least partly genetic. METHODS:Ordinal genome-wide association study of suicidality in the UK Biobank cohort comparing: 'no suicidality' controls (N = 83,557); 'thoughts that life was not worth living' (N = 21,063); 'ever contemplated self-harm' (N = 13,038); 'act of deliberate self-harm in the past' (N = 2498); and 'previous suicide attempt' (N = 2666). OUTCOMES:We identified three novel genome-wide significant loci for suicidality (on chromosomes nine, 11 and 13) and moderate-to-strong genetic correlations between suicidality and a range of psychiatric disorders, most notably depression (rg 0·81). INTERPRETATION:These findings provide new information about genetic variants relating to increased risk of suicidal thoughts and behaviours. Future work should assess the extent to which polygenic risk scores for suicidality, in combination with non-genetic risk factors, may be useful for stratified approaches to suicide prevention at a population level. FUND: UKRI Innovation-HDR-UK Fellowship (MR/S003061/1). MRC Mental Health Data Pathfinder Award (MC_PC_17217). MRC Doctoral Training Programme Studentship at the University of Glasgow (MR/K501335/1). MRC Doctoral Training Programme Studentship at the Universities of Glasgow and Edinburgh. UKRI Innovation Fellowship (MR/R024774/1)."
 30742608,https://doi.org/10.1371/journal.pcbi.1006785,"Assessing the performance of real-time epidemic forecasts: A case study of Ebola in the Western Area region of Sierra Leone, 2014-15.","Funk S, Camacho A, Kucharski AJ, Lowe R, Eggo RM, Edmunds WJ.","Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.",PLoS computational biology,2019,"Real-time forecasts based on mathematical models can inform critical decision-making during infectious disease outbreaks. Yet, epidemic forecasts are rarely evaluated during or after the event, and there is little guidance on the best metrics for assessment. Here, we propose an evaluation approach that disentangles different components of forecasting ability using metrics that separately assess the calibration, sharpness and bias of forecasts. This makes it possible to assess not just how close a forecast was to reality but also how well uncertainty has been quantified. We used this approach to analyse the performance of weekly forecasts we generated in real time for Western Area, Sierra Leone, during the 2013-16 Ebola epidemic in West Africa. We investigated a range of forecast model variants based on the model fits generated at the time with a semi-mechanistic model, and found that good probabilistic calibration was achievable at short time horizons of one or two weeks ahead but model predictions were increasingly unreliable at longer forecasting horizons. This suggests that forecasts may have been of good enough quality to inform decision making based on predictions a few weeks ahead of time but not longer, reflecting the high level of uncertainty in the processes driving the trajectory of the epidemic. Comparing forecasts based on the semi-mechanistic model to simpler null models showed that the best semi-mechanistic model variant performed better than the null models with respect to probabilistic calibration, and that this would have been identified from the earliest stages of the outbreak. As forecasts become a routine part of the toolkit in public health, standards for evaluation of performance will be important for assessing quality and improving credibility of mathematical models, and for elucidating difficulties and trade-offs when aiming to make the most useful and reliable forecasts."
@@ -18,19 +18,29 @@ id,doi,title,authorString,authorAffiliations,journalTitle,pubYear,abstract
 30120083,https://doi.org/10.1016/j.ebiom.2018.08.004,"Genome-Wide Association Study of Circadian Rhythmicity in 71,500 UK Biobank Participants and Polygenic Association with Mood Instability.","Ferguson A, Lyall LM, Ward J, Strawbridge RJ, Cullen B, Graham N, Niedzwiedz CL, Johnston KJA, MacKay D, Biello SM, Pell JP, Cavanagh J, McIntosh AM, Doherty A, Bailey MES, Lyall DM, Wyse CA, Smith DJ.","Institute of Health & Wellbeing, University of Glasgow, Scotland, UK. Electronic address: a.ferguson.3@research.gla.ac.uk.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK; Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Neuroscience and Psychology, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Scotland, UK.; Big Data Institute, Nuffield Department of Population Health, BHF Centre of Research Excellence, University of Oxford, Oxford, UK; Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.; School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Department of Molecular and Cellular Therapeutics, Irish Centre for Vascular Biology, Royal College of Surgeons in Ireland (RCSI), Dublin, Ireland.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK. Electronic address: Daniel.Smith@glasgow.ac.uk.",EBioMedicine,2018,"BACKGROUND:Circadian rhythms are fundamental to health and are particularly important for mental wellbeing. Disrupted rhythms of rest and activity are recognised as risk factors for major depressive disorder and bipolar disorder. METHODS:We conducted a genome-wide association study (GWAS) of low relative amplitude (RA), an objective measure of rest-activity cycles derived from the accelerometer data of 71,500 UK Biobank participants. Polygenic risk scores (PRS) for low RA were used to investigate potential associations with psychiatric phenotypes. OUTCOMES:Two independent genetic loci were associated with low RA, within genomic regions for Neurofascin (NFASC) and Solute Carrier Family 25 Member 17 (SLC25A17). A secondary GWAS of RA as a continuous measure identified a locus within Meis Homeobox 1 (MEIS1). There were no significant genetic correlations between low RA and any of the psychiatric phenotypes assessed. However, PRS for low RA was significantly associated with mood instability across multiple PRS thresholds (at PRS threshold 0·05: OR = 1·02, 95% CI = 1·01-1·02, p = 9·6 × 10-5), and with major depressive disorder (at PRS threshold 0·1: OR = 1·03, 95% CI = 1·01-1·05, p = 0·025) and neuroticism (at PRS threshold 0·5: Beta = 0·02, 95% CI = 0·007-0·04, p = 0·021). INTERPRETATION:Overall, our findings contribute new knowledge on the complex genetic architecture of circadian rhythmicity and suggest a putative biological link between disrupted circadian function and mood disorder phenotypes, particularly mood instability, but also major depressive disorder and neuroticism. FUNDING:Medical Research Council (MR/K501335/1)."
 29925668,https://doi.org/10.1136/jech-2017-210370,Emergency hospital admissions associated with a non-randomised housing intervention meeting national housing quality standards: a longitudinal data linkage study.,"Rodgers SE, Bailey R, Johnson R, Berridge D, Poortinga W, Lannon S, Smith R, Lyons RA.","Department of Public Health and Policy, University of Liverpool, Liverpool, UK.; Health Data Research-UK, Swansea University, Swansea, UK.; Health Data Research-UK, Swansea University, Swansea, UK.; Health Data Research-UK, Swansea University, Swansea, UK.; Welsh School of Architecture, Cardiff University, Cardiff, Wales, UK.; Welsh School of Architecture, Cardiff University, Cardiff, Wales, UK.; School of Geography and Planning, Cardiff University, Cardiff, Wales, UK.; Health Data Research-UK, Swansea University, Swansea, UK.",Journal of epidemiology and community health,2018,"BACKGROUND:We investigated tenant healthcare utilisation associated with upgrading 8558 council houses to a national quality standard. Homes received multiple internal and external improvements and were analysed using repeated measures of healthcare utilisation. METHODS:The primary outcome was emergency hospital admissions for cardiorespiratory conditions and injuries for residents aged 60 years and over. Secondary outcomes included each of the separate conditions, for tenants aged 60 and over, and for all ages. Council home address and intervention records for eight housing cointerventions were anonymously linked to demographic data, hospital admissions and deaths for individuals in a dynamic cohort. Counts of health events were analysed using multilevel regression models to investigate associations between receipt of each housing improvement, adjusting for potential confounding factors and regional trends. RESULTS:Residents aged 60 years and over living in homes when improvements were made were associated with up to 39% fewer admissions compared with those living in homes that were not upgraded (incidence rate ratio=0.61, 95% CI 0.53 to 0.72). Reduced admissions were associated with electrical systems, windows and doors, wall insulation, and garden paths. There were small non-significant reductions for the primary outcome associated with upgrading heating, adequate loft insulation, new kitchens and new bathrooms. CONCLUSION:Results suggest that hospital admissions can be avoided through improving whole home quality standards. This is the first large-scale longitudinal evaluation of a whole home intervention that has evaluated multiple improvement elements using individual-level objective routine health data."
 30649175,https://doi.org/10.1001/jamacardio.2018.4537,Cardiovascular Risk Factors Associated With Venous Thromboembolism.,"Gregson J, Kaptoge S, Bolton T, Pennells L, Willeit P, Burgess S, Bell S, Sweeting M, Rimm EB, Kabrhel C, Zöller B, Assmann G, Gudnason V, Folsom AR, Arndt V, Fletcher A, Norman PE, Nordestgaard BG, Kitamura A, Mahmoodi BK, Whincup PH, Knuiman M, Salomaa V, Meisinger C, Koenig W, Kavousi M, Völzke H, Cooper JA, Ninomiya T, Casiglia E, Rodriguez B, Ben-Shlomo Y, Després JP, Simons L, Barrett-Connor E, Björkelund C, Notdurfter M, Kromhout D, Price J, Sutherland SE, Sundström J, Kauhanen J, Gallacher J, Beulens JWJ, Dankner R, Cooper C, Giampaoli S, Deen JF, Gómez de la Cámara A, Kuller LH, Rosengren A, Svensson PJ, Nagel D, Crespo CJ, Brenner H, Albertorio-Diaz JR, Atkins R, Brunner EJ, Shipley M, Njølstad I, Lawlor DA, van der Schouw YT, Selmer RM, Trevisan M, Verschuren WMM, Greenland P, Wassertheil-Smoller S, Lowe GDO, Wood AM, Butterworth AS, Thompson SG, Danesh J, Di Angelantonio E, Meade T, Emerging Risk Factors Collaboration.","London School of Hygiene and Tropical Medicine, London, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; Harvard T. H. Chan School of Public Health, Boston, Massachusetts.; Massachusetts General Hospital, Boston.; Department of Clinical Sciences, Lund University, Malmö, Sweden.; Assmann Foundation for Prevention, Münster, Germany.; Icelandic Heart Association, Kópavogur, Iceland.; University of Minnesota School of Public Health, Minneapolis.; Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.; London School of Hygiene and Tropical Medicine, London, United Kingdom.; University of Western Australia, Perth, Western Australia, Australia.; Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark.; Osaka University, Osaka, Japan.; University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.; St George's, University of London, London, United Kingdom.; University of Western Australia, Perth, Western Australia, Australia.; National Institute for Health and Welfare, Helsinki, Finland.; Ludwig Maximilian University of Munich, Munich, Germany.; Deutsches Herzzentrum München, Technische Universität München, Munich, Germany.; Erasmus University Medical Center, Erasmus University, Rotterdam, the Netherlands.; University of Greifswald, Greifswald, Germany.; UCL Medical School, University College London, London, United Kingdom.; Kyushu University, Fukuoka, Japan.; University of Padova, Padua, Italy.; University of Hawaii, Honolulu.; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; Institute of Nutraceuticals and Functional Foods, Université Laval, Quebec, Quebec, Canada.; The University of New South Wales, Sydney, New South Wales, Australia.; University of California, San Diego.; University of Gothenburg, Gothenburg, Sweden.; Department of Internal Medicine, Bruneck Hospital, Bruneck, Italy.; University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.; University of Edinburgh, Edinburgh, United Kingdom.; Medical University of South Carolina, Charleston.; University of Greifswald, Greifswald, Germany.; Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; VU University Medical Center Amsterdam, Amsterdam, the Netherlands.; Tel Aviv University, Tel Aviv, Israel.; MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom.; National Institute of Health (ISS), Rome, Italy.; Center of Health Equity, Diversity and Inclusion, University of Washington School of Medicine, Seattle.; Clinical Research and Clinical Trials Unit, Plataforma de Innovación en Tecnologías Médicas y Sanitarias, Madrid, Spain.; University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.; University of Gothenburg, Gothenburg, Sweden.; Department of Clinical Sciences, Lund University, Malmö, Sweden.; Ludwig Maximilian University of Munich, Munich, Germany.; Portland State University, Portland, Oregon.; University of Minnesota School of Public Health, Minneapolis.; US Centers for Disease Control and Prevention, Atlanta, Georgia.; Monash University, Melbourne, Victoria, Australia.; Department of Epidemiology and Public Health, University College London, London, United Kingdom.; Department of Epidemiology and Public Health, University College London, London, United Kingdom.; Norwegian Institute of Public Health, Oslo, Norway.; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Norwegian Institute of Public Health, Oslo, Norway.; CUNY School of Medicine, City University of New York, New York.; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Feinberg School of Medicine, Northwestern University, Chicago, Illinois.; Albert Einstein College of Medicine, New York, New York.; Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; London School of Hygiene and Tropical Medicine, London, United Kingdom.",JAMA cardiology,2019,"Importance:It is uncertain to what extent established cardiovascular risk factors are associated with venous thromboembolism (VTE). Objective:To estimate the associations of major cardiovascular risk factors with VTE, ie, deep vein thrombosis and pulmonary embolism. Design, Setting, and Participants:This study included individual participant data mostly from essentially population-based cohort studies from the Emerging Risk Factors Collaboration (ERFC; 731 728 participants; 75 cohorts; years of baseline surveys, February 1960 to June 2008; latest date of follow-up, December 2015) and the UK Biobank (421 537 participants; years of baseline surveys, March 2006 to September 2010; latest date of follow-up, February 2016). Participants without cardiovascular disease at baseline were included. Data were analyzed from June 2017 to September 2018. Exposures:A panel of several established cardiovascular risk factors. Main Outcomes and Measures:Hazard ratios (HRs) per 1-SD higher usual risk factor levels (or presence/absence). Incident fatal outcomes in ERFC (VTE, 1041; coronary heart disease [CHD], 25 131) and incident fatal/nonfatal outcomes in UK Biobank (VTE, 2321; CHD, 3385). Hazard ratios were adjusted for age, sex, smoking status, diabetes, and body mass index (BMI). Results:Of the 731 728 participants from the ERFC, 403 396 (55.1%) were female, and the mean (SD) age at the time of the survey was 51.9 (9.0) years; of the 421 537 participants from the UK Biobank, 233 699 (55.4%) were female, and the mean (SD) age at the time of the survey was 56.4 (8.1) years. Risk factors for VTE included older age (ERFC: HR per decade, 2.67; 95% CI, 2.45-2.91; UK Biobank: HR, 1.81; 95% CI, 1.71-1.92), current smoking (ERFC: HR, 1.38; 95% CI, 1.20-1.58; UK Biobank: HR, 1.23; 95% CI, 1.08-1.40), and BMI (ERFC: HR per 1-SD higher BMI, 1.43; 95% CI, 1.35-1.50; UK Biobank: HR, 1.37; 95% CI, 1.32-1.41). For these factors, there were similar HRs for pulmonary embolism and deep vein thrombosis in UK Biobank (except adiposity was more strongly associated with pulmonary embolism) and similar HRs for unprovoked vs provoked VTE. Apart from adiposity, these risk factors were less strongly associated with VTE than CHD. There were inconsistent associations of VTEs with diabetes and blood pressure across ERFC and UK Biobank, and there was limited ability to study lipid and inflammation markers. Conclusions and Relevance:Older age, smoking, and adiposity were consistently associated with higher VTE risk."
+30351417,https://doi.org/10.1093/bioinformatics/bty837,pJRES Binning Algorithm (JBA): a new method to facilitate the recovery of metabolic information from pJRES 1H NMR spectra.,"Rodriguez-Martinez A, Ayala R, Posma JM, Harvey N, Jiménez B, Sonomura K, Sato TA, Matsuda F, Zalloua P, Gauguier D, Nicholson JK, Dumas ME.","Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, Imperial College London, London, UK.; Section of Structural Biology, Department of Medicine, Shimadzu Corporation, Kyoto, Japan.; Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, Imperial College London, London, UK.; Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, Imperial College London, London, UK.; Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, Imperial College London, London, UK.; Life Science Research Center, Technology Research Laboratory, Shimadzu Corporation, Kyoto, Japan.; Life Science Research Center, Technology Research Laboratory, Shimadzu Corporation, Kyoto, Japan.; Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.; School of Medicine, Lebanese American University, Beirut, Lebanon.; Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.; Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, Imperial College London, London, UK.; Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, Imperial College London, London, UK.","Bioinformatics (Oxford, England)",2019,"MOTIVATION:Data processing is a key bottleneck for 1H NMR-based metabolic profiling of complex biological mixtures, such as biofluids. These spectra typically contain several thousands of signals, corresponding to possibly few hundreds of metabolites. A number of binning-based methods have been proposed to reduce the dimensionality of 1 D 1H NMR datasets, including statistical recoupling of variables (SRV). Here, we introduce a new binning method, named JBA (""pJRES Binning Algorithm""), which aims to extend the applicability of SRV to pJRES spectra. RESULTS:The performance of JBA is comprehensively evaluated using 617 plasma 1H NMR spectra from the FGENTCARD cohort. The results presented here show that JBA exhibits higher sensitivity than SRV to detect peaks from low-abundance metabolites. In addition, JBA allows a more efficient removal of spectral variables corresponding to pure electronic noise, and this has a positive impact on multivariate model building. AVAILABILITY AND IMPLEMENTATION:The algorithm is implemented using the MWASTools R/Bioconductor package. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online."
+31101093,https://doi.org/10.1186/s12889-019-6888-9,Educational and health outcomes of children and adolescents receiving antiepileptic medication: Scotland-wide record linkage study of 766 244 schoolchildren.,"Fleming M, Fitton CA, Steiner MFC, McLay JS, Clark D, King A, Mackay DF, Pell JP.","Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK. michael.fleming@glasgow.ac.uk.; Department of Child Health, University of Aberdeen, Aberdeen, AB25 2ZG, UK.; Department of Child Health, University of Aberdeen, Aberdeen, AB25 2ZG, UK.; Department of Child Health, University of Aberdeen, Aberdeen, AB25 2ZG, UK.; Information Services Division, Edinburgh, EH12 9EB, UK.; ScotXed, Scottish Government, Edinburgh, EH6 6QQ, UK.; Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK.; Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK.",BMC public health,2019,"BACKGROUND:Childhood epilepsy can adversely affect education and employment in addition to health. Previous studies are small or highly selective producing conflicting results. This retrospective cohort study aims to compare educational and health outcomes of children receiving antiepileptic medication versus peers. METHODS:Record linkage of Scotland-wide databases covering dispensed prescriptions, acute and psychiatric hospitalisations, maternity records, deaths, annual pupil census, school absences/exclusions, special educational needs, school examinations, and (un)employment provided data on 766,244 children attending Scottish schools between 2009 and 2013. Outcomes were adjusted for sociodemographic and maternity confounders and comorbid conditions. RESULTS:Compared with peers, children on antiepileptic medication were more likely to experience school absence (Incidence Rate Ratio [IRR] 1.43, 95% CI: 1.38, 1.48), special educational needs (Odds ratio [OR] 9.60, 95% CI: 9.02, 10.23), achieve the lowest level of attainment (OR 3.43, 95% CI: 2.74, 4.29) be unemployed (OR 1.82, 95% CI: 1.60, 2.07), be admitted to hospital (Hazard Ratio [HR] 3.56, 95% CI: 3.42, 3.70), and die (HR 22.02, 95% CI: 17.00, 28.53). Absenteeism partly explained poorer attainment and higher unemployment. Girls and younger children on antiepileptic medication had higher risk of poor outcomes. CONCLUSIONS:Children on antiepileptic medication fare worse than peers across educational and health outcomes. In order to reduce school absenteeism and mitigate its effects, children with epilepsy should receive integrated care from a multidisciplinary team that spans education and healthcare."
 30984759,https://doi.org/10.3389/fmed.2019.00048,"Direct-to-Consumer Genetic Testing's Red Herring: ""Genetic Ancestry"" and Personalized Medicine.","Blell M, Hunter MA.","Policy, Ethics and Life Sciences Research Centre, School of Geography, Politics and Sociology, Newcastle University, Newcastle-upon-Tyne, United Kingdom.; Department of Philosophy, Logic, and Scientific Method, Centre for Philosophy of Natural and Social Science (CPNSS), The London School of Economics and Political Science, London, United Kingdom.",Frontiers in medicine,2019,"The growth in the direct-to-consumer genetic testing industry poses a number of challenges for healthcare practice, among a number of other areas of concern. Several companies providing this service send their customers reports including information variously referred to as genetic ethnicity, genetic heritage, biogeographic ancestry, and genetic ancestry. In this article, we argue that such information should not be used in healthcare consultations or to assess health risks. Far from representing a move toward personalized medicine, use of this information poses risks both to patients as individuals and to racialized ethnic groups because of the way it misrepresents human genetic diversity."
 31073125,https://doi.org/10.1038/s41533-019-0132-z,Systematic review of clinical prediction models to support the diagnosis of asthma in primary care.,"Daines L, McLean S, Buelo A, Lewis S, Sheikh A, Pinnock H.","Asthma UK Centre for Applied Research, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK. luke.daines@ed.ac.uk.; Asthma UK Centre for Applied Research, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.; Scottish Collaboration for Public Health Research and Policy, The University of Edinburgh, Edinburgh, UK.; Edinburgh Clinical Trials Unit, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.; Asthma UK Centre for Applied Research, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.; Asthma UK Centre for Applied Research, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.",NPJ primary care respiratory medicine,2019,"Diagnosing asthma is challenging. Misdiagnosis can lead to untreated symptoms, incorrect treatment and avoidable deaths. The best combination of clinical features and tests to achieve a diagnosis of asthma is unclear. As asthma is usually diagnosed in non-specialist settings, a clinical prediction model to aid the assessment of the probability of asthma in primary care may improve diagnostic accuracy. We aimed to identify and describe existing prediction models to support the diagnosis of asthma in children and adults in primary care. We searched Medline, Embase, CINAHL, TRIP and US National Guidelines Clearinghouse databases from 1 January 1990 to 23 November 17. We included prediction models designed for use in primary care or equivalent settings to aid the diagnostic decision-making of clinicians assessing patients with symptoms suggesting asthma. Two reviewers independently screened titles, abstracts and full texts for eligibility, extracted data and assessed risk of bias. From 13,798 records, 53 full-text articles were reviewed. We included seven modelling studies; all were at high risk of bias. Model performance varied, and the area under the receiving operating characteristic curve ranged from 0.61 to 0.82. Patient-reported wheeze, symptom variability and history of allergy or allergic rhinitis were associated with asthma. In conclusion, clinical prediction models may support the diagnosis of asthma in primary care, but existing models are at high risk of bias and thus unreliable for informing practice. Future studies should adhere to recognised standards, conduct model validation and include a broader range of clinical data to derive a prediction model of value for clinicians."
 30772400,https://doi.org/10.1016/j.neuroimage.2019.02.028,Hierarchical complexity of the adult human structural connectome.,"Smith K, Bastin ME, Cox SR, Valdés Hernández MC, Wiseman S, Escudero J, Sudlow C.","Usher Institute for Population Health Science and Informatics, Medical School, University of Edinburgh, Edinburgh, EH16 4UX, UK. Electronic address: k.smith@ed.ac.uk.; Centre for Clinical Brain Sciences, Western General Hospital, University of Edinburgh, Edinburgh, EH4 2XU, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.; Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.; Centre for Clinical Brain Sciences, Western General Hospital, University of Edinburgh, Edinburgh, EH4 2XU, UK; Row Fogo Centre into Ageing and the Brain, Edinburgh Dementia Research Institute, University of Edinburgh, Edinburgh, EH16 4SB, UK.; Centre for Clinical Brain Sciences, Western General Hospital, University of Edinburgh, Edinburgh, EH4 2XU, UK.; School of Engineering, Institute for Digital Communications, University of Edinburgh, Edinburgh, EH9 3FB, UK.; Usher Institute for Population Health Science and Informatics, Medical School, University of Edinburgh, Edinburgh, EH16 4UX, UK.",NeuroImage,2019,"The structural network of the human brain has a rich topology which many have sought to characterise using standard network science measures and concepts. However, this characterisation remains incomplete and the non-obvious features of this topology have largely confounded attempts towards comprehensive constructive modelling. This calls for new perspectives. Hierarchical complexity is an emerging paradigm of complex network topology based on the observation that complex systems are composed of hierarchies within which the roles of hierarchically equivalent nodes display highly variable connectivity patterns. Here we test the hierarchical complexity of the human structural connectomes of a group of seventy-nine healthy adults. Binary connectomes are found to be more hierarchically complex than three benchmark random network models. This provides a new key description of brain structure, revealing a rich diversity of connectivity patterns within hierarchically equivalent nodes. Dividing the connectomes into four tiers based on degree magnitudes indicates that the most complex nodes are neither those with the highest nor lowest degrees but are instead found in the middle tiers. Spatial mapping of the brain regions in each hierarchical tier reveals consistency with the current anatomical, functional and neuropsychological knowledge of the human brain. The most complex tier (Tier 3) involves regions believed to bridge high-order cognitive (Tier 1) and low-order sensorimotor processing (Tier 2). We then show that such diversity of connectivity patterns aligns with the diversity of functional roles played out across the brain, demonstrating that hierarchical complexity can characterise functional diversity strictly from the network topology."
+31171806,https://doi.org/10.1038/s41598-019-44907-8,On neighbourhood degree sequences of complex networks.,Smith KM.,"Usher Institute of Population Health Science and Informatics, University of Edinburgh, 9 BioQuarter, Little France, Edinburgh, EH16 4UX, UK. k.smith@ed.ac.uk.",Scientific reports,2019,"Network topology is a fundamental aspect of network science that allows us to gather insights into the complicated relational architectures of the world we inhabit. We provide a first specific study of neighbourhood degree sequences in complex networks. We consider how to explicitly characterise important physical concepts such as similarity, heterogeneity and organization in these sequences, as well as updating the notion of hierarchical complexity to reflect previously unnoticed organizational principles. We also point out that neighbourhood degree sequences are related to a powerful subtree kernel for unlabeled graph classification. We study these newly defined sequence properties in a comprehensive array of graph models and over 200 real-world networks. We find that these indices are neither highly correlated with each other nor with classical network indices. Importantly, the sequences of a wide variety of real world networks are found to have greater similarity and organisation than is expected for networks of their given degree distributions. Notably, while biological, social and technological networks all showed consistently large neighbourhood similarity and organisation, hierarchical complexity was not a consistent feature of real world networks. Neighbourhood degree sequences are an interesting tool for describing unique and important characteristics of complex networks."
 30921401,https://doi.org/10.1371/journal.pone.0214607,Effect of impregnated central venous catheters on thrombosis in paediatric intensive care: Post-hoc analyses of the CATCH trial.,"Wu Y, Fraser C, Gilbert R, Mok Q.","University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom.; Population, Policy and Practice Programme, NIHR Biomedical Research Centre, University College London Great Ormond Street Institute of Child Health, London, United Kingdom.; Population, Policy and Practice Programme, NIHR Biomedical Research Centre, University College London Great Ormond Street Institute of Child Health, London, United Kingdom.; Paediatric Intensive Care Unit, Great Ormond Street Hospital for Children, London, United Kingdom.",PloS one,2019,"PURPOSE:The CATheter infections in CHildren (CATCH) trial reported reduced risks of bloodstream infection with antibiotic impregnated compared with heparin-bonded or standard central venous catheters (CVC) in paediatric intensive care. CVC impregnation did not increase the risk of thrombosis which was recorded in 24% of participants. This post-hoc analysis determines the effect of CVC impregnation on the risk of thrombosis leading to CVC removal or swollen limb. METHODS:We analysed patients in the CATCH trial, blind to CVC allocation, to define clinically relevant thrombosis based on the clinical sign most frequently recorded in patients where the CVC was removed because of concerns regarding thrombosis. In post-hoc, three-way comparisons of antibiotic, heparin and standard CVCs, we determined the effect of CVC type on time to clinically relevant thrombosis, using Cox proportional hazards regression. RESULTS:Of 1409 participants with a successful CVC insertion, the sign most frequently resulting in CVC removal was swollen limb (37.6%; 41/109), with lower rates of removal of CVC following 2 episodes of difficulty withdrawing blood or of flushing to unblock the CVC. In intention to treat analyses (n = 1485), clinically relevant thrombosis, defined by 1 or more record of swollen limb or CVC removal due to concerns about thrombosis, was recorded in 11.9% (58/486) of antibiotic CVCs, 12.1% (60/497) of heparin CVCs, and 10.2% (51/502) of standard CVCs. We found no differences in time to clinically relevant thrombosis according to type of CVC. CONCLUSIONS:We found no evidence for an increased risk of clinically relevant thrombosis in antibiotic impregnated compared to heparin-bonded or standard CVCs in children receiving intensive care."
 30835202,https://doi.org/10.7554/eLife.43657,An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome.,"Richardson TG, Harrison S, Hemani G, Davey Smith G.","MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.",eLife,2019,"The age of large-scale genome-wide association studies (GWAS) has provided us with an unprecedented opportunity to evaluate the genetic liability of complex disease using polygenic risk scores (PRS). In this study, we have analysed 162 PRS (p<5×10-05) derived from GWAS and 551 heritable traits from the UK Biobank study (N = 334,398). Findings can be investigated using a web application (http:‌//‌mrcieu.‌mrsoftware.org/‌PRS‌_atlas/), which we envisage will help uncover both known and novel mechanisms which contribute towards disease susceptibility. To demonstrate this, we have investigated the results from a phenome-wide evaluation of schizophrenia genetic liability. Amongst findings were inverse associations with measures of cognitive function which extensive follow-up analyses using Mendelian randomization (MR) provided evidence of a causal relationship. We have also investigated the effect of multiple risk factors on disease using mediation and multivariable MR frameworks. Our atlas provides a resource for future endeavours seeking to unravel the causal determinants of complex disease."
+30729733,https://doi.org/10.1111/ijpo.12512,Predictors of objectively measured physical activity in 12-month-old infants: A study of linked birth cohort data with electronic health records.,"Raza H, Zhou SM, Todd C, Christian D, Marchant E, Morgan K, Khanom A, Hill R, Lyons RA, Brophy S.","The School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Department of Sport and Physical Activity, Edge Hill University, Ormskirk, UK.; Health Data Research UK, Swansea University, Swansea, UK.; DECIPHer, School of Social Sciences, Cardiff University, Cardiff, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Abertawe Bro Morgannwg University Health Board (ABM UHB), Port Talbot, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.",Pediatric obesity,2019,"BACKGROUND:Physical activity (PA) levels are associated with long-term health, and levels of PA when young are predictive of adult activity levels. OBJECTIVES:This study examines factors associated with PA levels in 12-month infants. METHOD:One hundred forty-one mother-infant pairs were recruited via a longitudinal birth cohort study (April 2010 to March 2013). The PA level was collected using accelerometers and linked to postnatal notes and electronic medical records via the Secure Anonymised Information Linkage databank. Univariable and multivariable linear regressions were used to examine the factors associated with PA levels. RESULTS:Using univariable analysis, higher PA was associated with the following (P value less than 0.05): being male, larger infant size, healthy maternal blood pressure levels, full-term gestation period, higher consumption of vegetables (infant), lower consumption of juice (infant), low consumption of adult crisps (infant), longer breastfeeding duration, and more movement during sleep (infant) but fewer night wakings. Combined into a multivariable regression model (R2  = 0.654), all factors remained significant, showing lower PA levels were associated with female gender, smaller infant, preterm birth, higher maternal blood pressure, low vegetable consumption, high crisp consumption, and less night movement. CONCLUSION:The PA levels of infants were strongly associated with both gestational and postnatal environmental factors. Healthy behaviours appear to cluster, and a healthy diet was associated with a more active infant. Boys were substantially more active than girls, even at age 12 months. These findings can help inform interventions to promote healthier lives for infants and to understand the determinants of their PA levels."
+30659777,https://doi.org/10.1111/ijpo.12505,Are children with clinical obesity at increased risk of inpatient hospital admissions? An analysis using linked electronic health records in the UK millennium cohort study.,"Griffiths LJ, Cortina-Borja M, Bandyopadhyay A, Tingay K, De Stavola BL, Bedford H, Akbari A, Firman N, Lyons RA, Dezateux C.","Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; National Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, UK.; Administrative Data Research Centre Wales, Swansea University Medical School, Swansea, UK.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.",Pediatric obesity,2019,"BACKGROUND:Few studies have examined health service utilization of children with overweight or obesity by using linked electronic health records (EHRs). OBJECTIVE/METHODS:We analysed EHRs from 3269 children (1678 boys; 51.3% [weighted]) participating in the Millennium Cohort Study, living in Wales or Scotland at age seven whose parents consented to record linkage. We used height and weight measurements at age five to categorize children as obese (>98th centile) or overweight (>91st centile) (UK1990 clinical reference standards) and linked to hospital admissions, up to age 14 years, in the Patient Episode Database for Wales and Scottish Morbidity Records. Negative binomial regression models compared rates of inpatient admissions by weight status at age five. RESULTS:At age five, 11.5% and 6.7% of children were overweight or obese, respectively; 1221 (38%) children were subsequently admitted to hospital at least once. Admissions were not increased among children with overweight or obesity (adjusted rate ratio [RR], 95% confidence interval [CI]: 0.87, 0.68-1.10 and 1.16, 0.87-1.54, respectively). CONCLUSIONS:In this nationally representative cohort of children in Wales and Scotland, those with overweight or obesity at entry to primary school did not have increased rates of hospital admissions in later childhood and early adolescence."
+31220083,https://doi.org/10.1371/journal.pmed.1002833,Associations of genetically determined iron status across the phenome: A mendelian randomization study.,"Gill D, Benyamin B, Moore LSP, Monori G, Zhou A, Koskeridis F, Evangelou E, Laffan M, Walker AP, Tsilidis KK, Dehghan A, Elliott P, Hyppönen E, Tzoulaki I.","Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Australian Centre for Precision Health, University of South Australia, Adelaide, Australia.; National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Australian Centre for Precision Health, University of South Australia, Adelaide, Australia.; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Centre for Haematology, Imperial College London, United Kingdom.; Population Science & Experimental Medicine, Institute of Cardiovascular Science, University College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Australian Centre for Precision Health, University of South Australia, Adelaide, Australia.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.",PLoS medicine,2019,"BACKGROUND:Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status. METHODS AND FINDINGS:Genome-wide association study (GWAS) summary data obtained from 48,972 European individuals (55% female) across 19 cohorts in the Genetics of Iron Status Consortium were used to identify 3 genetic variants (rs1800562 and rs1799945 in the hemochromatosis gene [HFE] and rs855791 in the transmembrane protease serine 6 gene [TMPRSS6]) that associate with increased serum iron, ferritin, and transferrin saturation and decreased transferrin levels, thus serving as instruments for systemic iron status. Phenome-wide association study (PheWAS) of these instruments was performed on 424,439 European individuals (54% female) in the UK Biobank who were aged 40-69 years when recruited from 2006 to 2010, with their genetic data linked to Hospital Episode Statistics (HES) from April, 1995 to March, 2016. Two-sample summary data mendelian randomization (MR) analysis was performed to investigate the effect of varying iron status on outcomes across the human phenome. MR-PheWAS analysis for the 3 iron status genetic instruments was performed separately and then pooled by meta-analysis. Correction was made for testing of multiple correlated phenotypes using a 5% false discovery rate (FDR) threshold. Heterogeneity between MR estimates for different instruments was used to indicate possible bias due to effects of the genetic variants through pathways unrelated to iron status. There were 904 distinct phenotypes included in the MR-PheWAS analyses. After correcting for multiple testing, the 3 genetic instruments for systemic iron status demonstrated consistent evidence of a causal effect of higher iron status on decreasing risk of traits related to anemia (iron deficiency anemia: odds ratio [OR] scaled to a standard deviation [SD] increase in genetically determined serum iron levels 0.72, 95% confidence interval [CI] 0.64-0.81, P = 4 × 10-8) and hypercholesterolemia (hypercholesterolemia: OR 0.88, 95% CI 0.83-0.93, P = 2 × 10-5) and increasing risk of traits related to infection of the skin and related structures (cellulitis and abscess of the leg: OR 1.25, 95% CI 1.10-1.42, P = 6 × 10-4). The main limitations of this study relate to possible bias from pleiotropic effects of the considered genetic variants and misclassification of diagnoses in the HES data. Furthermore, this work only investigated participants with European ancestry, and the findings may not be applicable to other ethnic groups. CONCLUSIONS:Our findings offer novel, to our knowledge, insight into previously unreported effects of iron status, highlighting a potential protective effect of higher iron status on hypercholesterolemia and a detrimental role on risk of skin and skin structure infections. Given the modifiable and variable nature of iron status, these findings warrant further investigation."
+31115347,https://doi.org/10.2196/12412,Health Data Processes: A Framework for Analyzing and Discussing Efficient Use and Reuse of Health Data With a Focus on Patient-Reported Outcome Measures.,"Hjollund NHI, Valderas JM, Kyte D, Calvert MJ.","Occupational Medicine, University Research Clinic, AmbuFlex/WestChronic, Aarhus University, Herning, Denmark.; University of Exeter Collaboration for Academic Primary Care, Health Services & Policy Research Group, National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care (South West Peninsula), University of Exeter, Exeter, United Kingdom.; Centre for Patient Reported Outcomes Research, Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham, United Kingdom.; Centre for Patient Reported Outcomes Research, Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham, United Kingdom.",Journal of medical Internet research,2019,"The collection and use of patient health data are central to any kind of activity in the health care system. These data may be produced during routine clinical processes or obtained directly from the patient using patient-reported outcome (PRO) measures. Although efficiency and other reasons justify data availability for a range of potentially relevant uses, these data are nearly always collected for a single specific purpose. The health care literature reflects this narrow scope, and there is limited literature on the joint use of health data for daily clinical use, clinical research, surveillance, and administrative purposes. The aim of this paper is to provide a framework for discussing the efficient use of health data with a specific focus on the role of PRO measures. PRO data may be used at an individual patient level to inform patient care or shared decision making and to tailor care to individual needs or group-level needs as a complement to health record data, such as that on mortality and readmission, in order to inform service delivery and measure the real-world effectiveness of treatment. PRO measures may be used either for their own sake, to provide valuable information from the patient perspective, or as a proxy for clinical data that would otherwise not be feasible to collect. We introduce a framework to analyze any health care activity that involves health data. The framework consists of four data processes (patient identification, data collection, data aggregation and data use), further structured into two dichotomous dimensions in each data process (level: group vs patient; timeframe: ad hoc vs systematic). This framework is used to analyze various health activities with respect to joint use of data, considering the technical, legal, organizational, and logistical challenges that characterize each data process. Finally, we propose a model for joint use of health data with data collected during follow-up as a base. Demands for health data will continue to increase, which will further add to the need for the concerted use and reuse of PRO data for parallel purposes. Repeated and uncoordinated PRO data collection for the same patient for different purposes results in misuse of resources for the patient and the health care system as well as reduced response rates owing to questionnaire fatigue. PRO data can be routinely collected both at the hospital (from inpatients as well as outpatients) and outside of hospital settings; in primary or social care settings; or in the patient's home, provided the health informatics infrastructure is in place. In the future, clinical settings are likely to be a prominent source of PRO data; however, we are also likely to see increased remote collection of PRO data by patients in their own home (telePRO). Data collection for research and quality surveillance will have to adapt to this circumstance and adopt complementary data capture methods that take advantage of the utility of PRO data collected during daily clinical practice. The European Union's regulation with respect to the protection of personal data-General Data Protection Regulation-imposes severe restrictions on the use of health data for parallel purposes, and steps should be taken to alleviate the consequences while still protecting personal data against misuse."
 30183734,https://doi.org/10.1371/journal.pone.0202359,Time spent at blood pressure target and the risk of death and cardiovascular diseases.,"Chung SC, Pujades-Rodriguez M, Duyx B, Denaxas SC, Pasea L, Hingorani A, Timmis A, Williams B, Hemingway H.","Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Institute of Cardiovascular Science, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.",PloS one,2018,"BACKGROUND:The time a patient spends with blood pressure at target level is an intuitive measure of successful BP management, but population studies on its effectiveness are as yet unavailable. METHOD:We identified a population-based cohort of 169,082 individuals with newly identified high blood pressure who were free of cardiovascular disease from January 1997 to March 2010. We used 1.64 million clinical blood pressure readings to calculate the TIme at TaRgEt (TITRE) based on current target blood pressure levels. RESULT:The median (Inter-quartile range) TITRE among all patients was 2.8 (0.3, 5.6) months per year, only 1077 (0.6%) patients had a TITRE ≥11 months. Compared to people with a 0% TITRE, patients with a TITRE of 3-5.9 months, and 6-8.9 months had 75% and 78% lower odds of the composite of cardiovascular death, myocardial infarction and stroke (adjusted odds ratios, 0.25 (95% confidence interval: 0.21, 0.31) and 0.22 (0.17, 0.27), respectively). These associations were consistent for heart failure and any cardiovascular disease and death (comparing a 3-5.9 month to 0% TITRE, 63% and 60% lower in odds, respectively), among people who did or did not have blood pressure 'controlled' on a single occasion during the first year of follow-up, and across groups defined by number of follow-up BP measure categories. CONCLUSION:Based on the current frequency of measurement of blood pressure this study suggests that few newly hypertensive patients sustained a complete, year-round on target blood pressure over time. The inverse associations between a higher TITRE and lower risk of incident cardiovascular diseases were independent of widely-used blood pressure 'control' indicators. Randomized trials are required to evaluate interventions to increase a person's time spent at blood pressure target."
 30774489,https://doi.org/10.2147/PROM.S162802,The use of patient-reported outcome research in modern ophthalmology: impact on clinical trials and routine clinical practice.,"Braithwaite T, Calvert M, Gray A, Pesudovs K, Denniston AK.","Centre for Patient Reported Outcomes Research and NIHR Birmingham Biomedical Research Centre, University of Birmingham, Edgbaston, Birmingham, UK, tasaneebraithwaite@gmail.com.; Centre for Patient Reported Outcomes Research and NIHR Birmingham Biomedical Research Centre, University of Birmingham, Edgbaston, Birmingham, UK, tasaneebraithwaite@gmail.com.; Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Consultant, Adelaide, SA, Australia.; Centre for Patient Reported Outcomes Research and NIHR Birmingham Biomedical Research Centre, University of Birmingham, Edgbaston, Birmingham, UK, tasaneebraithwaite@gmail.com.",Patient related outcome measures,2019,"This review article considers the rising demand for patient-reported outcome measures (PROMs) in modern ophthalmic research and clinical practice. We review what PROMs are, how they are developed and chosen for use, and how their quality can be critically appraised. We outline the progress made to develop PROMs in each clinical subspecialty. We highlight recent examples of the use of PROMs as secondary outcome measures in randomized controlled clinical trials and consider the impact they have had. With increasing interest in using PROMs as primary outcome measures, particularly where interventions have been found to be of equivalent efficacy by traditional outcome metrics, we highlight the importance of instrument precision in permitting smaller sample sizes to be recruited. Our review finds that while there has been considerable progress in PROM development, particularly in cataract, glaucoma, medical retina, and low vision, there is a paucity of useful tools for less common ophthalmic conditions. Development and validation of item banks, administered using computer adaptive testing, has been proposed as a solution to overcome many of the traditional limitations of PROMs, but further work will be needed to examine their acceptability to patients, clinicians, and investigators."
 30909231,https://doi.org/10.3233/JAD-181085,A Meta-Analysis of Alzheimer's Disease Brain Transcriptomic Data.,"Patel H, Dobson RJB, Newhouse SJ.","Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.",Journal of Alzheimer's disease : JAD,2019,"BACKGROUND:Microarray technologies have identified imbalances in the expression of specific genes and biological pathways in Alzheimer's disease (AD) brains. However, there is a lack of reproducibility across individual AD studies, and many related neurodegenerative and mental health disorders exhibit similar perturbations. OBJECTIVE:Meta-analyze publicly available transcriptomic data from multiple brain-related disorders to identify robust transcriptomic changes specific to AD brains. METHODS:Twenty-two AD, eight schizophrenia, five bipolar disorder, four Huntington's disease, two major depressive disorder, and one Parkinson's disease dataset totaling 2,667 samples and mapping to four different brain regions (temporal lobe, frontal lobe, parietal lobe, and cerebellum) were analyzed. Differential expression analysis was performed independently in each dataset, followed by meta-analysis using a combining p-value method known as Adaptively Weighted with One-sided Correction. RESULTS:Meta-analysis identified 323, 435, 1,023, and 828 differentially expressed genes specific to the AD temporal lobe, frontal lobe, parietal lobe, and cerebellum brain regions, respectively. Seven of these genes were consistently perturbed across all AD brain regions with SPCS1 gene expression pattern replicating in RNA-Seq data. A further nineteen genes were perturbed specifically in AD brain regions affected by both plaques and tangles, suggesting possible involvement in AD neuropathology. In addition, biological pathways involved in the ""metabolism of proteins"" and viral components were significantly enriched across AD brains. CONCLUSION:This study identified transcriptomic changes specific to AD brains, which could make a significant contribution toward the understanding of AD disease mechanisms and may also provide new therapeutic targets."
+31122927,https://doi.org/10.1136/bmj.l1778,Determinants of the decline in mortality from acute stroke in England: linked national database study of 795 869 adults.,"Seminog OO, Scarborough P, Wright FL, Rayner M, Goldacre MJ.","Unit of Health-Care Epidemiology, Big Data Institute, Nuffield Department of Population Health, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford OX3 7LF, UK olena.seminog@ndph.ox.ac.uk.; Centre on Population Approaches for Non-communicable Disease Prevention, Nuffield Department of Population Health, NIHR Biomedical Research Centre at Oxford, University of Oxford, Oxford, UK.; Unit of Health-Care Epidemiology, Big Data Institute, Nuffield Department of Population Health, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford OX3 7LF, UK.; Centre on Population Approaches for Non-communicable Disease Prevention, Nuffield Department of Population Health, NIHR Biomedical Research Centre at Oxford, University of Oxford, Oxford, UK.; Unit of Health-Care Epidemiology, Big Data Institute, Nuffield Department of Population Health, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford OX3 7LF, UK.",BMJ (Clinical research ed.),2019,"OBJECTIVES:To study trends in stroke mortality rates, event rates, and case fatality, and to explain the extent to which the reduction in stroke mortality rates was influenced by changes in stroke event rates or case fatality. DESIGN:Population based study. SETTING:Person linked routine hospital and mortality data, England. PARTICIPANTS:795 869 adults aged 20 and older who were admitted to hospital with acute stroke or died from stroke. MAIN OUTCOME MEASURES:Stroke mortality rates, stroke event rates (stroke admission or stroke death without admission), and case fatality within 30 days after stroke. RESULTS:Between 2001 and 2010 stroke mortality rates decreased by 55%, stroke event rates by 20%, and case fatality by 40%. The study population included 358 599 (45%) men and 437 270 (55%) women. Average annual change in mortality rate was -6.0% (95% confidence interval -6.2% to -5.8%) in men and -6.1% (-6.3% to -6.0%) in women, in stroke event rate was -1.3% (-1.4% to -1.2%) in men and -2.1% (-2.2 to -2.0) in women, and in case fatality was -4.7% (-4.9% to -4.5%) in men and -4.4% (-4.5% to -4.2%) in women. Mortality and case fatality but not event rate declined in all age groups: the stroke event rate decreased in older people but increased by 2% each year in adults aged 35 to 54 years. Of the total decline in mortality rates, 71% was attributed to the decline in case fatality (78% in men and 66% in women) and the remainder to the reduction in stroke event rates. The contribution of the two factors varied between age groups. Whereas the reduction in mortality rates in people younger than 55 years was due to the reduction in case fatality, in the oldest age group (≥85 years) reductions in case fatality and event rates contributed nearly equally. CONCLUSIONS:Declines in case fatality, probably driven by improvements in stroke care, contributed more than declines in event rates to the overall reduction in stroke mortality. Mortality reduction in men and women younger than 55 was solely a result of a decrease in case fatality, whereas stroke event rates increased in the age group 35 to 54 years. The increase in stroke event rates in young adults is a concern. This suggests that stroke prevention needs to be strengthened to reduce the occurrence of stroke in people younger than 55 years."
+31005938,https://doi.org/10.1136/bmjopen-2018-027289,"Longitudinal access and exposure to green-blue spaces and individual-level mental health and well-being: protocol for a longitudinal, population-wide record-linked natural experiment.","Mizen A, Song J, Fry R, Akbari A, Berridge D, Parker SC, Johnson R, Lovell R, Lyons RA, Nieuwenhuijsen M, Stratton G, Wheeler BW, White J, White M, Rodgers SE.","Swansea University Medical School, Swansea University, Swansea, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; European Centre for Environment and Human Health, University of Exeter Medical School, Knowledge Spa, Royal Cornwall Hospital, Cornwall, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; Instituto de Salud Global de Barcelona.c/ Rosselló, 132, 5º 2ª, Barcelona, Spain.; Research Centre in Applied Sports, Technology Exercise and Medicine, College of Engineering, Swansea University, Swansea, UK.; European Centre for Environment and Human Health, University of Exeter Medical School, Knowledge Spa, Royal Cornwall Hospital, Cornwall, UK.; DECIPHer, Centre for Trials Research, Cardiff University, Cardiff, UK.; European Centre for Environment and Human Health, University of Exeter Medical School, Knowledge Spa, Royal Cornwall Hospital, Cornwall, UK.; Swansea University Medical School, Swansea University, Swansea, UK.",BMJ open,2019,"INTRODUCTION:Studies suggest that access and exposure to green-blue spaces (GBS) have beneficial impacts on mental health. However, the evidence base is limited with respect to longitudinal studies. The main aim of this longitudinal, population-wide, record-linked natural experiment, is to model the daily lived experience by linking GBS accessibility indices, residential GBS exposure and health data; to enable quantification of the impact of GBS on well-being and common mental health disorders, for a national population. METHODS AND ANALYSIS:This research will estimate the impact of neighbourhood GBS access, GBS exposure and visits to GBS on the risk of common mental health conditions and the opportunity for promoting subjective well-being (SWB); both key priorities for public health. We will use a Geographic Information System (GIS) to create quarterly household GBS accessibility indices and GBS exposure using digital map and satellite data for 1.4 million homes in Wales, UK (2008-2018). We will link the GBS accessibility indices and GBS exposures to individual-level mental health outcomes for 1.7 million people with general practitioner (GP) data and data from the National Survey for Wales (n=~12 000) on well-being in the Secure Anonymised Information Linkage (SAIL) Databank. We will examine if these associations are modified by multiple sociophysical variables, migration and socioeconomic disadvantage. Subgroup analyses will examine associations by different types of GBS. This longitudinal study will be augmented by cross-sectional research using survey data on self-reported visits to GBS and SWB. ETHICS AND DISSEMINATION:All data will be anonymised and linked within the privacy protecting SAIL Databank. We will be using anonymised data and therefore we are exempt from National Research Ethics Committee (NREC). An Information Governance Review Panel (IGRP) application (Project ID: 0562) to link these data has been approved.The research programme will be undertaken in close collaboration with public/patient involvement groups. A multistrategy programme of dissemination is planned with the academic community, policy-makers, practitioners and the public."
 30999919,https://doi.org/10.1186/s12911-019-0805-0,Identifying clinically important COPD sub-types using data-driven approaches in primary care population based electronic health records.,"Pikoula M, Quint JK, Nissen F, Hemingway H, Smeeth L, Denaxas S.","Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK. m.pikoula@ucl.ac.uk.; Health Data Research UK London, University College London, 222 Euston Road, London, NW1 2DA, UK.; Health Data Research UK London, University College London, 222 Euston Road, London, NW1 2DA, UK.; Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK.; Health Data Research UK London, University College London, 222 Euston Road, London, NW1 2DA, UK.; Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK.",BMC medical informatics and decision making,2019,"BACKGROUND:COPD is a highly heterogeneous disease composed of different phenotypes with different aetiological and prognostic profiles and current classification systems do not fully capture this heterogeneity. In this study we sought to discover, describe and validate COPD subtypes using cluster analysis on data derived from electronic health records. METHODS:We applied two unsupervised learning algorithms (k-means and hierarchical clustering) in 30,961 current and former smokers diagnosed with COPD, using linked national structured electronic health records in England available through the CALIBER resource. We used 15 clinical features, including risk factors and comorbidities and performed dimensionality reduction using multiple correspondence analysis. We compared the association between cluster membership and COPD exacerbations and respiratory and cardiovascular death with 10,736 deaths recorded over 146,466 person-years of follow-up. We also implemented and tested a process to assign unseen patients into clusters using a decision tree classifier. RESULTS:We identified and characterized five COPD patient clusters with distinct patient characteristics with respect to demographics, comorbidities, risk of death and exacerbations. The four subgroups were associated with 1) anxiety/depression; 2) severe airflow obstruction and frailty; 3) cardiovascular disease and diabetes and 4) obesity/atopy. A fifth cluster was associated with low prevalence of most comorbid conditions. CONCLUSIONS:COPD patients can be sub-classified into groups with differing risk factors, comorbidities, and prognosis, based on data included in their primary care records. The identified clusters confirm findings of previous clustering studies and draw attention to anxiety and depression as important drivers of the disease in young, female patients."
 30969971,https://doi.org/10.1371/journal.pone.0213435,Are active children and young people at increased risk of injuries resulting in hospital admission or accident and emergency department attendance? Analysis of linked cohort and electronic hospital records in Wales and Scotland.,"Griffiths LJ, Cortina-Borja M, Tingay K, Bandyopadhyay A, Akbari A, DeStavola BL, Bedford H, Lyons RA, Dezateux C.","Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, United Kingdom.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.; Administrative Data Research Centre Wales, Swansea University Medical School, Swansea, United Kingdom.; National Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, United Kingdom.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, United Kingdom.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, United Kingdom.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.",PloS one,2019,"INTRODUCTION:Children and young people (CYP) are encouraged to increase time spent being physically active, especially in moderate and vigorous intensity pursuits. However, there is limited evidence on the prospective association of activity levels with injuries resulting in use of hospital services. We examined the relationship between objectively-measured physical activity (PA) and subsequent injuries resulting in hospital admissions or accident and emergency department (A&E) attendances, using linked electronic hospital records (EHR) from a nationally representative prospective cohort of CYP in Wales and Scotland. METHODS:We analysed accelerometer-based estimates of moderate to vigorous (MVPA) and vigorous PA (VPA) from 1,585 (777 [46%] boys) seven-year-old Millennium Cohort Study members, living in Wales or Scotland, whose parents consented to linkage of cohort records to EHRs up until their 14th birthday. Negative binomial regression models adjusted by potential individual, household and area-level confounders, were fitted to estimate associations between average daily minutes of MVPA, and VPA (in 10-minute increments), and number of injury-related hospital admissions and/or A&E attendances from age nine to 14 years. RESULTS:CYP spent a median of 59.5 and 18.1 minutes in MVPA and VPA/day respectively, with boys significantly more active than girls; 47.3% of children experienced at least one injury-related admission or A&E attendance during the study period. Rates of injury-related hospital admission and/or A&E attendance were positively associated with MVPA and VPA in boys but not in girls: respective adjusted incidence rate ratios (95% CI) for boys: 1.09 (1.01, 1.17) and 1.16 (1.00, 1.34), and for girls: 0.94 (0.86, 1.03) and 0.85 (0.69, 1.04). CONCLUSION:Boys but not girls who engage in more intense PA at age seven years are at higher risk of injury-related hospital admission or A&E attendance when aged nine to 14 years than their less active peers. This may reflect gender differences in the type and associated risks of activities undertaken. EHRs can make a useful contribution to injury surveillance and prevention if routinely augmented with information on context and setting of the injuries sustained. Injury prevention initiatives should not discourage engagement in PA and outdoor play given their over-riding health and social benefits."
 29743285,https://doi.org/10.1136/bmj.k1717,Risk of stroke and transient ischaemic attack in patients with a diagnosis of resolved atrial fibrillation: retrospective cohort studies.,"Adderley NJ, Nirantharakumar K, Marshall T.","Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.; Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK K.Nirantharan@bham.ac.uk.; Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.",BMJ (Clinical research ed.),2018,"OBJECTIVES:To determine rates of stroke or transient ischaemic attack (TIA) and all cause mortality in patients with a diagnosis of ""resolved"" atrial fibrillation compared to patients with unresolved atrial fibrillation and without atrial fibrillation. DESIGN:Two retrospective cohort studies. SETTING:General practices contributing to The Health Improvement Network, 1 January 2000 to 15 May 2016. PARTICIPANTS:Adults aged 18 years or more with no previous stroke or TIA: 11 159 with resolved atrial fibrillation, 15 059 controls with atrial fibrillation, and 22 266 controls without atrial fibrillation. MAIN OUTCOME MEASURES:Primary outcome was incidence of stroke or TIA. Secondary outcome was all cause mortality. RESULTS:Adjusted incidence rate ratios for stroke or TIA in patients with resolved atrial fibrillation were 0.76 (95% confidence interval 0.67 to 0.85, P<0.001) versus controls with atrial fibrillation and 1.63 (1.46 to 1.83, P<0.001) versus controls without atrial fibrillation. Adjusted incidence rate ratios for mortality in patients with resolved atrial fibrillation were 0.60 (0.56 to 0.65, P<0.001) versus controls with atrial fibrillation and 1.13 (1.06 to 1.21, P<0.001) versus controls without atrial fibrillation. When patients with resolved atrial fibrillation and documented recurrent atrial fibrillation were excluded the adjusted incidence rate ratio for stroke or TIA was 1.45 (1.26 to 1.67, P<0.001) versus controls without atrial fibrillation. CONCLUSION:Patients with resolved atrial fibrillation remain at higher risk of stroke or TIA than patients without atrial fibrillation. The risk is increased even in those in whom recurrent atrial fibrillation is not documented. Guidelines should be updated to advocate continued use of anticoagulants in patients with resolved atrial fibrillation."
 30814958,https://doi.org/10.3389/fpsyt.2019.00036,Risk Assessment Tools and Data-Driven Approaches for Predicting and Preventing Suicidal Behavior.,"Velupillai S, Hadlaczky G, Baca-Garcia E, Gorrell GM, Werbeloff N, Nguyen D, Patel R, Leightley D, Downs J, Hotopf M, Dutta R.","Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.; National Center for Suicide Research and Prevention (NASP), Department of Learning, Informatics, Management and Ethics (LIME), Karolinska Institutet, Stockholm, Sweden.; Department of Psychiatry, IIS-Jimenez Diaz Foundation, Madrid, Spain.; Department of Computer Science, University of Sheffield, Sheffield, United Kingdom.; Division of Psychiatry, University College London, London, United Kingdom.; Alan Turing Institute, London, United Kingdom.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.",Frontiers in Psychiatry,2019,"Risk assessment of suicidal behavior is a time-consuming but notoriously inaccurate activity for mental health services globally. In the last 50 years a large number of tools have been designed for suicide risk assessment, and tested in a wide variety of populations, but studies show that these tools suffer from low positive predictive values. More recently, advances in research fields such as machine learning and natural language processing applied on large datasets have shown promising results for health care, and may enable an important shift in advancing precision medicine. In this conceptual review, we discuss established risk assessment tools and examples of novel data-driven approaches that have been used for identification of suicidal behavior and risk. We provide a perspective on the strengths and weaknesses of these applications to mental health-related data, and suggest research directions to enable improvement in clinical practice."
 29899974,https://doi.org/10.12688/f1000research.13830.2,Knowledge discovery for Deep Phenotyping serious mental illness from Electronic Mental Health records.,"Jackson R, Patel R, Velupillai S, Gkotsis G, Hoyle D, Stewart R.","Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.; Independent Researcher, Manchester, UK.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.",F1000Research,2018,"We demonstrate a scalable approach to discovering new depictions of SMI symptomatology based on real world clinical observation. Such approaches may offer the opportunity to consider broader manifestations of SMI symptomatology than is typically assessed via current diagnostic frameworks, and create the potential for enhancing nomenclatures such as SNOMED CT based on real world depictions."
+30585256,https://doi.org/10.1038/s41416-018-0365-6,"Personal radio use and cancer risks among 48,518 British police officers and staff from the Airwave Health Monitoring Study.","Gao H, Aresu M, Vergnaud AC, McRobie D, Spear J, Heard A, Kongsgård HW, Singh D, Muller DC, Elliott P.","Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Faculty of Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK. p.elliott@imperial.ac.uk.",British journal of cancer,2019,"BACKGROUND:Radiofrequency electromagnetic fields (RF-EMF) from mobile phones have been classified as potentially carcinogenic. No study has investigated use of Terrestrial Trunked Radio (TETRA), a source of RF-EMF with wide occupational use, and cancer risks. METHODS:We investigated association of monthly personal radio use and risk of cancer using Cox proportional hazards regression among 48,518 police officers and staff of the Airwave Health Monitoring Study in Great Britain. RESULTS:During median follow-up of 5.9 years, 716 incident cancer cases were identified. Among users, the median of the average monthly duration of use in the year prior to enrolment was 30.5  min (inter-quartile range 8.1, 68.1). Overall, there was no association between personal radio use and risk of all cancers (hazard ratio [HR] = 0.98, 95% confidence interval [CI]: 0.93, 1.03). For head and neck cancers HR = 0.72 (95% CI: 0.30, 1.70) among personal radio users vs non-users, and among users it was 1.06 (95% CI: 0.91, 1.23) per doubling of minutes of personal radio use. CONCLUSIONS:With the limited follow-up to date, we found no evidence of association of personal radio use with cancer risk. Continued follow-up of the cohort is warranted."
 30524708,https://doi.org/10.1093/ckj/sfy090,The potential for improving cardio-renal outcomes by sodium-glucose co-transporter-2 inhibition in people with chronic kidney disease: a rationale for the EMPA-KIDNEY study.,"Herrington WG, Preiss D, Haynes R, von Eynatten M, Staplin N, Hauske SJ, George JT, Green JB, Landray MJ, Baigent C, Wanner C.","Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Boehringer Ingelheim International, Ingelheim, Germany.; Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Boehringer Ingelheim International, Ingelheim, Germany.; Boehringer Ingelheim International, Ingelheim, Germany.; Duke Clinical Research Institute, Duke University Medical Center, Durham, NC, USA.; Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Würzburg University Clinic, Würzburg, Germany.",Clinical Kidney Journal,2018,"Diabetes is a common cause of chronic kidney disease (CKD), but in aggregate, non-diabetic diseases account for a higher proportion of cases of CKD than diabetes in many parts of the world. Inhibition of the renin-angiotensin system reduces the risk of kidney disease progression and treatments that lower blood pressure (BP) or low-density lipoprotein cholesterol reduce cardiovascular (CV) risk in this population. Nevertheless, despite such interventions, considerable risks for kidney and CV complications remain. Recently, large placebo-controlled outcome trials have shown that sodium-glucose co-transporter-2 (SGLT-2) inhibitors reduce the risk of CV disease (including CV death and hospitalization for heart failure) in people with type 2 diabetes who are at high risk of atherosclerotic disease, and these effects were largely independent of improvements in hyperglycaemia, BP and body weight. In the kidney, increased sodium delivery to the macula densa mediated by SGLT-2 inhibition has the potential to reduce intraglomerular pressure, which may explain why SGLT-2 inhibitors reduce albuminuria and appear to slow kidney function decline in people with diabetes. Importantly, in the trials completed to date, these benefits appeared to be maintained at lower levels of kidney function, despite attenuation of glycosuric effects, and did not appear to be dependent on ambient hyperglycaemia. There is therefore a rationale for studying the cardio-renal effects of SGLT-2 inhibition in people at risk of CV disease and hyperfiltration (i.e. those with substantially reduced nephron mass and/or albuminuria), irrespective of whether they have diabetes."
 30082368,https://doi.org/10.1136/bmjopen-2018-024755,Validating injury burden estimates using population birth cohorts and longitudinal cohort studies of injury outcomes: the VIBES-Junior study protocol.,"Gabbe BJ, Dipnall JF, Lynch JW, Rivara FP, Lyons RA, Ameratunga S, Brussoni M, Lecky FE, Bradley C, Simpson PM, Beck B, Demmler JC, Lyons J, Schneeberg A, Harrison JE.","School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; School of Public Health, University of Adelaide, Adelaide, South Australia, Australia.; Departments of Pediatrics and Epidemiology, and the Harborview Injury Prevention and Research Center, University of Washington, Seattle, Washington, USA.; Health Data Research UK, Swansea University, Swansea, UK.; School of Population Health, University of Auckland, Auckland, New Zealand.; Department of Pediatrics, School of Population and Public Health, University of British Columbia, Vancouver, Canada.; School of Health and Related Research, University of Sheffield, Sheffield, UK.; South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia.; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.; British Columbia Injury Research and Prevention Unit, Children's Hospital Research Institute, Vancouver, Canada.; Research Centre for Injury Studies, Flinders University, Adelaide, South Australia, Australia.",BMJ open,2018,"Traumatic injury is a leading contributor to the global disease burden in children and adolescents, but methods used to estimate burden do not account for differences in patterns of injury and recovery between children and adults. A lack of empirical data on postinjury disability in children has limited capacity to derive valid disability weights and describe the long-term individual and societal impacts of injury in the early part of life. The aim of this study is to establish valid estimates of the burden of non-fatal injury in children and adolescents.Five longitudinal studies of paediatric injury survivors <18 years at the time of injury (Australia, Canada, UK and USA) and two whole-of-population linked administrative data paediatric studies (Australia and Wales) will be analysed over a 3-year period commencing 2018. Meta-analysis of deidentified patient-level data (n≈2,600) from five injury-specific longitudinal studies (Victorian State Trauma Registry; Victorian Orthopaedic Trauma Outcomes Registry; UK Burden of Injury; British Columbia Children's Hospital Longitudinal Injury Outcomes; Children's Health After Injury) and >1 million children from two whole-of-population cohorts (South Australian Early Childhood Data Project and Wales Electronic Cohort for Children). Systematic analysis of pooled injury-specific cohort data using a variety of statistical techniques, and parallel analysis of whole-of-population cohorts, will be used to develop estimated disability weights for years lost due to disability, establish appropriate injury classifications and explore factors influencing recovery.The project was approved by the Monash University Human Research Ethics Committee project number 12 311. Results of this study will be submitted for publication in internationally peer-reviewed journals. The findings from this project have the capacity to improve the validity of paediatric injury burden measurements in future local and global burden of disease studies."
 30801036,https://doi.org/10.12688/wellcomeopenres.15007.1,Million Migrants study of healthcare and mortality outcomes in non-EU migrants and refugees to England: Analysis protocol for a linked population-based cohort study of 1.5 million migrants.,"Burns R, Pathak N, Campos-Matos I, Zenner D, Vittal Katikireddi S, Muzyamba MC, Miranda JJ, Gilbert R, Rutter H, Jones L, Williamson E, Hayward AC, Smeeth L, Abubakar I, Hemingway H, Aldridge RW.","Centre for Public Health Data Science, University College London, London, UK.; Centre for Public Health Data Science, University College London, London, UK.; Public Health England, London, UK.; Migration Health Division, International Organization for Migration, Brussels, Belgium.; MRC/CSO Social and Public Health Sciences Unit, Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.; Public Health England, London, UK.; CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.; Institute of Epidemiology and Healthcare, University College London, London, UK.; Faculty of Humanities and Social Sciences, University of Bath, Bath, UK.; UK programme manager, Doctors of the World, London, UK.; Faculty of Epidemiology & Population Health, London School of Hygiene and Tropical Medicine, London, UK.; Institute of Epidemiology and Healthcare, University College London, London, UK.; Department of Non-Communicable Diseases Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.; Institute for Global Health, University College London, London, UK.; Institute of Health Informatics Research, Faculty of Population Health Sciences, University College London, London, UK.; Centre for Public Health Data Science, University College London, London, UK.",Wellcome open research,2019,"Background: In 2017, 15.6% of the people living in England were born abroad, yet we have a limited understanding of their use of health services and subsequent health conditions. This linked population-based cohort study aims to describe the hospital-based healthcare and mortality outcomes of 1.5 million non-European Union (EU) migrants and refugees in England. Methods and analysis: We will link four data sources: first, non-EU migrant tuberculosis pre-entry screening data; second, refugee pre-entry health assessment data; third, national hospital episode statistics; and fourth, Office of National Statistics death records. Using this linked dataset, we will then generate a population-based cohort to examine hospital-based events and mortality outcomes in England between Jan 1, 2006, and Dec 31, 2017. We will compare outcomes across three groups in our analyses: 1) non-EU international migrants, 2) refugees, and 3) general population of England. Ethics and dissemination: We will obtain approval to use unconsented patient identifiable data from the Secretary of State for Health through the Confidentiality Advisory Group and the National Health Service Research Ethics Committee. After data linkage, we will destroy identifying data and undertake all analyses using the pseudonymised dataset. The results will provide policy makers and civil society with detailed information about the health needs of non-EU international migrants and refugees in England."
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@@ -6,28 +6,32 @@ id,doi,title,authorString,authorAffiliations,journalTitle,pubYear,abstract
 31109684,https://doi.org/10.1016/j.injury.2019.05.004,Agreement between medical record and administrative coding of common comorbidities in orthopaedic trauma patients.,"Daly S, Nguyen TQ, Gabbe BJ, Braaf S, Simpson P, Ekegren CL.","School of Medicine, Monash University, Melbourne, VIC, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia; Health Data Research, UK.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia. Electronic address: christina.ekegren@monash.edu.",Injury,2019,"OBJECTIVE:To i) quantify the agreement between comorbidities documented within medical records and an orthopaedic trauma dataset; and ii) compare agreement between these sources before and after the introduction of new comorbidity coding rules in Australian hospitals. STUDY DESIGN AND SETTING:A random sample of adult (≥ 16 years) orthopaedic trauma patients (n = 400) were extracted from the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR). Diagnoses of obesity, arthritis, diabetes and cardiac conditions documented within patients' medical records were compared to ICD-10-AM comorbidity codes (provided by hospitals) for the same admission. Agreement was calculated (Cohen's kappa) before and after the introduction of new coding rules. RESULTS:All comorbidities had the same or higher prevalence in medical record data compared to coded data. Kappa values ranged from <0.001 (poor agreement) for coronary artery disease to 0.94 (excellent agreement) for type 2 diabetes. There was improvement in agreement between sources for most conditions following the introduction of new coding rules. CONCLUSION:There has been improvement in the coding of certain comorbidities since the introduction of new coding rules, suggesting that, since 2015, administrative data has improved capacity to capture patients' comorbidity profiles. Consideration must be taken when using the ICD-10-AM data due to its limitations."
 30999919,https://doi.org/10.1186/s12911-019-0805-0,Identifying clinically important COPD sub-types using data-driven approaches in primary care population based electronic health records.,"Pikoula M, Quint JK, Nissen F, Hemingway H, Smeeth L, Denaxas S.","Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK. m.pikoula@ucl.ac.uk.; Health Data Research UK London, University College London, 222 Euston Road, London, NW1 2DA, UK.; Health Data Research UK London, University College London, 222 Euston Road, London, NW1 2DA, UK.; Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK.; Health Data Research UK London, University College London, 222 Euston Road, London, NW1 2DA, UK.; Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK.",BMC medical informatics and decision making,2019,"BACKGROUND:COPD is a highly heterogeneous disease composed of different phenotypes with different aetiological and prognostic profiles and current classification systems do not fully capture this heterogeneity. In this study we sought to discover, describe and validate COPD subtypes using cluster analysis on data derived from electronic health records. METHODS:We applied two unsupervised learning algorithms (k-means and hierarchical clustering) in 30,961 current and former smokers diagnosed with COPD, using linked national structured electronic health records in England available through the CALIBER resource. We used 15 clinical features, including risk factors and comorbidities and performed dimensionality reduction using multiple correspondence analysis. We compared the association between cluster membership and COPD exacerbations and respiratory and cardiovascular death with 10,736 deaths recorded over 146,466 person-years of follow-up. We also implemented and tested a process to assign unseen patients into clusters using a decision tree classifier. RESULTS:We identified and characterized five COPD patient clusters with distinct patient characteristics with respect to demographics, comorbidities, risk of death and exacerbations. The four subgroups were associated with 1) anxiety/depression; 2) severe airflow obstruction and frailty; 3) cardiovascular disease and diabetes and 4) obesity/atopy. A fifth cluster was associated with low prevalence of most comorbid conditions. CONCLUSIONS:COPD patients can be sub-classified into groups with differing risk factors, comorbidities, and prognosis, based on data included in their primary care records. The identified clusters confirm findings of previous clustering studies and draw attention to anxiety and depression as important drivers of the disease in young, female patients."
 29925668,https://doi.org/10.1136/jech-2017-210370,Emergency hospital admissions associated with a non-randomised housing intervention meeting national housing quality standards: a longitudinal data linkage study.,"Rodgers SE, Bailey R, Johnson R, Berridge D, Poortinga W, Lannon S, Smith R, Lyons RA.","Department of Public Health and Policy, University of Liverpool, Liverpool, UK.; Health Data Research-UK, Swansea University, Swansea, UK.; Health Data Research-UK, Swansea University, Swansea, UK.; Health Data Research-UK, Swansea University, Swansea, UK.; Welsh School of Architecture, Cardiff University, Cardiff, Wales, UK.; Welsh School of Architecture, Cardiff University, Cardiff, Wales, UK.; School of Geography and Planning, Cardiff University, Cardiff, Wales, UK.; Health Data Research-UK, Swansea University, Swansea, UK.",Journal of epidemiology and community health,2018,"BACKGROUND:We investigated tenant healthcare utilisation associated with upgrading 8558 council houses to a national quality standard. Homes received multiple internal and external improvements and were analysed using repeated measures of healthcare utilisation. METHODS:The primary outcome was emergency hospital admissions for cardiorespiratory conditions and injuries for residents aged 60 years and over. Secondary outcomes included each of the separate conditions, for tenants aged 60 and over, and for all ages. Council home address and intervention records for eight housing cointerventions were anonymously linked to demographic data, hospital admissions and deaths for individuals in a dynamic cohort. Counts of health events were analysed using multilevel regression models to investigate associations between receipt of each housing improvement, adjusting for potential confounding factors and regional trends. RESULTS:Residents aged 60 years and over living in homes when improvements were made were associated with up to 39% fewer admissions compared with those living in homes that were not upgraded (incidence rate ratio=0.61, 95% CI 0.53 to 0.72). Reduced admissions were associated with electrical systems, windows and doors, wall insulation, and garden paths. There were small non-significant reductions for the primary outcome associated with upgrading heating, adequate loft insulation, new kitchens and new bathrooms. CONCLUSION:Results suggest that hospital admissions can be avoided through improving whole home quality standards. This is the first large-scale longitudinal evaluation of a whole home intervention that has evaluated multiple improvement elements using individual-level objective routine health data."
-30729733,https://doi.org/10.1111/ijpo.12512,Predictors of objectively measured physical activity in 12-month-old infants: A study of linked birth cohort data with electronic health records.,"Raza H, Zhou SM, Todd C, Christian D, Marchant E, Morgan K, Khanom A, Hill R, Lyons RA, Brophy S.","The School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Department of Sport and Physical Activity, Edge Hill University, Ormskirk, UK.; Health Data Research UK, Swansea University, Swansea, UK.; DECIPHer, School of Social Sciences, Cardiff University, Cardiff, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Abertawe Bro Morgannwg University Health Board (ABM UHB), Port Talbot, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.",Pediatric obesity,2019,"BACKGROUND:Physical activity (PA) levels are associated with long-term health, and levels of PA when young are predictive of adult activity levels. OBJECTIVES:This study examines factors associated with PA levels in 12-month infants. METHOD:One hundred forty-one mother-infant pairs were recruited via a longitudinal birth cohort study (April 2010 to March 2013). The PA level was collected using accelerometers and linked to postnatal notes and electronic medical records via the Secure Anonymised Information Linkage databank. Univariable and multivariable linear regressions were used to examine the factors associated with PA levels. RESULTS:Using univariable analysis, higher PA was associated with the following (P value less than 0.05): being male, larger infant size, healthy maternal blood pressure levels, full-term gestation period, higher consumption of vegetables (infant), lower consumption of juice (infant), low consumption of adult crisps (infant), longer breastfeeding duration, and more movement during sleep (infant) but fewer night wakings. Combined into a multivariable regression model (R2  = 0.654), all factors remained significant, showing lower PA levels were associated with female gender, smaller infant, preterm birth, higher maternal blood pressure, low vegetable consumption, high crisp consumption, and less night movement. CONCLUSION:The PA levels of infants were strongly associated with both gestational and postnatal environmental factors. Healthy behaviours appear to cluster, and a healthy diet was associated with a more active infant. Boys were substantially more active than girls, even at age 12 months. These findings can help inform interventions to promote healthier lives for infants and to understand the determinants of their PA levels."
-30969971,https://doi.org/10.1371/journal.pone.0213435,Are active children and young people at increased risk of injuries resulting in hospital admission or accident and emergency department attendance? Analysis of linked cohort and electronic hospital records in Wales and Scotland.,"Griffiths LJ, Cortina-Borja M, Tingay K, Bandyopadhyay A, Akbari A, DeStavola BL, Bedford H, Lyons RA, Dezateux C.","Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, United Kingdom.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.; Administrative Data Research Centre Wales, Swansea University Medical School, Swansea, United Kingdom.; National Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, United Kingdom.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, United Kingdom.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, United Kingdom.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.",PloS one,2019,"INTRODUCTION:Children and young people (CYP) are encouraged to increase time spent being physically active, especially in moderate and vigorous intensity pursuits. However, there is limited evidence on the prospective association of activity levels with injuries resulting in use of hospital services. We examined the relationship between objectively-measured physical activity (PA) and subsequent injuries resulting in hospital admissions or accident and emergency department (A&E) attendances, using linked electronic hospital records (EHR) from a nationally representative prospective cohort of CYP in Wales and Scotland. METHODS:We analysed accelerometer-based estimates of moderate to vigorous (MVPA) and vigorous PA (VPA) from 1,585 (777 [46%] boys) seven-year-old Millennium Cohort Study members, living in Wales or Scotland, whose parents consented to linkage of cohort records to EHRs up until their 14th birthday. Negative binomial regression models adjusted by potential individual, household and area-level confounders, were fitted to estimate associations between average daily minutes of MVPA, and VPA (in 10-minute increments), and number of injury-related hospital admissions and/or A&E attendances from age nine to 14 years. RESULTS:CYP spent a median of 59.5 and 18.1 minutes in MVPA and VPA/day respectively, with boys significantly more active than girls; 47.3% of children experienced at least one injury-related admission or A&E attendance during the study period. Rates of injury-related hospital admission and/or A&E attendance were positively associated with MVPA and VPA in boys but not in girls: respective adjusted incidence rate ratios (95% CI) for boys: 1.09 (1.01, 1.17) and 1.16 (1.00, 1.34), and for girls: 0.94 (0.86, 1.03) and 0.85 (0.69, 1.04). CONCLUSION:Boys but not girls who engage in more intense PA at age seven years are at higher risk of injury-related hospital admission or A&E attendance when aged nine to 14 years than their less active peers. This may reflect gender differences in the type and associated risks of activities undertaken. EHRs can make a useful contribution to injury surveillance and prevention if routinely augmented with information on context and setting of the injuries sustained. Injury prevention initiatives should not discourage engagement in PA and outdoor play given their over-riding health and social benefits."
 30444743,https://doi.org/10.1097/ccm.0000000000003424,"Risk Factors for 1-Year Mortality and Hospital Utilization Patterns in Critical Care Survivors: A Retrospective, Observational, Population-Based Data Linkage Study.","Szakmany T, Walters AM, Pugh R, Battle C, Berridge DM, Lyons RA.","Division of Population Medicine, Department of Anaesthesia, Intensive Care and Pain Medicine, Cardiff University, Heath Park Campus, Cardiff, United Kingdom.; Health Data Research UK, Swansea University Medical School, Data Science Building, Swansea, United Kingdom.; Department of Anaesthetic, Glan Clywdd Hospital, Betsi Cadwaladar University Health Board, Bodelwyddan, Rhyl, United Kingdom.; Morriston Hospital, Abertawe Bro Morgannwg University Health Board, Heol Maes Eglwys, Swansea, United Kingdom.; Health Data Research UK, Swansea University Medical School, Data Science Building, Swansea, United Kingdom.; Health Data Research UK, Swansea University Medical School, Data Science Building, Swansea, United Kingdom.",Critical care medicine,2019,"OBJECTIVES:Clear understanding of the long-term consequences of critical care survivorship is essential. We investigated the care process and individual factors associated with long-term mortality among ICU survivors and explored hospital use in this group. DESIGN:Population-based data linkage study using the Secure Anonymised Information Linkage databank. SETTING:All ICUs between 2006 and 2013 in Wales, United Kingdom. PATIENTS:We identified 40,631 patients discharged alive from Welsh adult ICUs. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:Primary outcome was 365-day survival. The secondary outcomes were 30- and 90-day survival and hospital utilization in the 365 days following ICU discharge. Kaplan-Meier curves were plotted to compare survival rates. Cox proportional hazards regression models were used to determine risk factors of mortality. Seven-thousand eight-hundred eighty-three patients (19.4%) died during the 1-year follow-up period. In the multivariable Cox regression analysis, advanced age and comorbidities were significant determinants of long-term mortality. Expedited discharge due to ICU bed shortage was associated with higher risk. The rate of hospitalization in the year prior to the critical care admission was 28 hospitalized days/1,000 d; post critical care was 88 hospitalized days/1,000 d for those who were still alive; and 57 hospitalized days/1,000 d and 412 hospitalized days/1,000 d for those who died by the end of the study, respectively. CONCLUSIONS:One in five ICU survivors die within 1 year, with advanced age and comorbidity being significant predictors of outcome, leading to high resource use. Care process factors indicating high system stress were associated with increased risk. More detailed understanding is needed on the effects of the potentially modifiable factors to optimize service delivery and improve long-term outcomes of the critically ill."
+30969971,https://doi.org/10.1371/journal.pone.0213435,Are active children and young people at increased risk of injuries resulting in hospital admission or accident and emergency department attendance? Analysis of linked cohort and electronic hospital records in Wales and Scotland.,"Griffiths LJ, Cortina-Borja M, Tingay K, Bandyopadhyay A, Akbari A, DeStavola BL, Bedford H, Lyons RA, Dezateux C.","Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, United Kingdom.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.; Administrative Data Research Centre Wales, Swansea University Medical School, Swansea, United Kingdom.; National Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, United Kingdom.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, United Kingdom.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, United Kingdom.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.",PloS one,2019,"INTRODUCTION:Children and young people (CYP) are encouraged to increase time spent being physically active, especially in moderate and vigorous intensity pursuits. However, there is limited evidence on the prospective association of activity levels with injuries resulting in use of hospital services. We examined the relationship between objectively-measured physical activity (PA) and subsequent injuries resulting in hospital admissions or accident and emergency department (A&E) attendances, using linked electronic hospital records (EHR) from a nationally representative prospective cohort of CYP in Wales and Scotland. METHODS:We analysed accelerometer-based estimates of moderate to vigorous (MVPA) and vigorous PA (VPA) from 1,585 (777 [46%] boys) seven-year-old Millennium Cohort Study members, living in Wales or Scotland, whose parents consented to linkage of cohort records to EHRs up until their 14th birthday. Negative binomial regression models adjusted by potential individual, household and area-level confounders, were fitted to estimate associations between average daily minutes of MVPA, and VPA (in 10-minute increments), and number of injury-related hospital admissions and/or A&E attendances from age nine to 14 years. RESULTS:CYP spent a median of 59.5 and 18.1 minutes in MVPA and VPA/day respectively, with boys significantly more active than girls; 47.3% of children experienced at least one injury-related admission or A&E attendance during the study period. Rates of injury-related hospital admission and/or A&E attendance were positively associated with MVPA and VPA in boys but not in girls: respective adjusted incidence rate ratios (95% CI) for boys: 1.09 (1.01, 1.17) and 1.16 (1.00, 1.34), and for girls: 0.94 (0.86, 1.03) and 0.85 (0.69, 1.04). CONCLUSION:Boys but not girls who engage in more intense PA at age seven years are at higher risk of injury-related hospital admission or A&E attendance when aged nine to 14 years than their less active peers. This may reflect gender differences in the type and associated risks of activities undertaken. EHRs can make a useful contribution to injury surveillance and prevention if routinely augmented with information on context and setting of the injuries sustained. Injury prevention initiatives should not discourage engagement in PA and outdoor play given their over-riding health and social benefits."
 31053412,https://doi.org/10.1016/j.burns.2019.04.006,Severe burns in Australian and New Zealand adults: Epidemiology and burn centre care.,"Toppi J, Cleland H, Gabbe B.","Monash University, Department of Epidemiology and Preventive Medicine, Melbourne, Victoria, Australia. Electronic address: jttoppi1@gmail.com.; Monash University, Department of Epidemiology and Preventive Medicine, Melbourne, Victoria, Australia; The Victorian Adult Burns Unit, The Alfred Hospital, Melbourne, Victoria, Australia; Department of Surgery, Monash University Central Clinical School, Melbourne, Victoria, Australia.; Monash University, Department of Epidemiology and Preventive Medicine, Melbourne, Victoria, Australia; Health Data Research UK, Swansea UniversityMedical School, Swansea University, Swansea, United Kingdom.",Burns : journal of the International Society for Burn Injuries,2019,"INTRODUCTION:Studies describing the epidemiology of severe burns (>20% total body surface area) in adults are limited despite the extensive associated morbidity and mortality. This study aimed to describe the epidemiology of severe burn injuries admitted to burn centres in Australia and New Zealand. MATERIALS AND METHODS:Data from the Burns Registry of Australia and New Zealand (BRANZ) were used in this study. Patients were eligible for inclusion if they were admitted between August 2009 and June 2013, were adults (18-years or older), and had burns of 20% total body surface area (TBSA) or greater. Demographics, burn characteristics and in-hospital mortality risk factors were investigated using multivariable Cox proportional hazards analysis. RESULTS:There were 496 BRANZ registered patients who met the inclusion criteria. Over half of the patients were aged 18-40 years and most were male. The median (IQR) TBSA was 31 (25-47). Most (75%) patients had burns involving <50% TBSA, 58% sustained their burn injury at home, and 86% had sustained flame burns. Leisure activities, working for income and preparing food together accounted for over 48% of the activities undertaken at the time of injury. The in-hospital mortality rate was 17% and the median (IQR) length of stay was 24 (12-44) days. Seventy-two percent were admitted to an intensive care unit (ICU) and 40% of patients had an associated inhalation injury. Alcohol and/or drug involvement was suspected in 25% of cases. CONCLUSION:This study describes the demographics, burn injury characteristics and in-hospital outcomes of severe burn injuries in adults whilst also identifying key predictors of inpatient mortality. Key findings included the over-representation of young males, intentional self-harm injuries and flame as a cause of burns and highlights high risk groups to help aid in the development of targeted prevention strategies."
 30887727,https://doi.org/10.1002/ppul.24314,Physical activity among children with asthma: Cross-sectional analysis in the UK millennium cohort.,"Pike KC, Griffiths LJ, Dezateux C, Pearce A.","Infection, Immunity and Inflammation Academic Programme, Great Ormond Street Institute of Child Health, University College London, London, UK.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Centre for Primary Care and Public Health, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.",Pediatric pulmonology,2019,"BACKGROUND:Although beneficial for health and well-being, most children do not achieve recommended levels of physical activity. Evidence for children with asthma is mixed, with symptom severity rarely considered. This paper aimed to address this gap. METHODS:We analyzed cross-sectional associations between physical activity and parent-reported asthma symptoms and severity for 6497 UK Millennium Cohort Study 7-year-old participants (3321, [49%] girls). Primary outcomes were daily moderate-to-vigorous physical activity (MVPA, minutes) and proportion of children achieving recommended minimum daily levels of 60 minutes of MVPA. Daily steps, sedentary time, and total activity counts per minute (cpm) were recorded, as were parent-reported asthma symptoms, medications, and recent hospital admissions. Associations were investigated using quantile (continuous outcomes) and Poisson (binary outcomes) regression, adjusting for demographic, socioeconomic, health, and environmental factors. RESULTS:Neither asthma status nor severity was associated with MVPA; children recently hospitalized for asthma were less likely to achieve recommended daily MVPA (risk ratio [95% confidence interval [CI]]: 0.67 [0.44, 1.03]). Recent wheeze, current asthma, and severe asthma symptoms were associated with fewer sedentary hours (difference in medians [95% CI]: -0.18 [-0.27, -0.08]; -0.14 [-0.24, -0.05]; -0.15, [-0.28, -0.02], respectively) and hospital admission with lower total activity (-48 cpm [-68, -28]). CONCLUSION:Children with asthma are as physically active as their asthma-free counterparts, while those recently hospitalized for asthma are less active. Qualitative studies are needed to understand the perceptions of children and families about physical activity following hospital admission and to inform support and advice needed to maintain active lifestyles for children with asthma."
-30659777,https://doi.org/10.1111/ijpo.12505,Are children with clinical obesity at increased risk of inpatient hospital admissions? An analysis using linked electronic health records in the UK millennium cohort study.,"Griffiths LJ, Cortina-Borja M, Bandyopadhyay A, Tingay K, De Stavola BL, Bedford H, Akbari A, Firman N, Lyons RA, Dezateux C.","Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; National Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, UK.; Administrative Data Research Centre Wales, Swansea University Medical School, Swansea, UK.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.",Pediatric obesity,2019,"BACKGROUND:Few studies have examined health service utilization of children with overweight or obesity by using linked electronic health records (EHRs). OBJECTIVE/METHODS:We analysed EHRs from 3269 children (1678 boys; 51.3% [weighted]) participating in the Millennium Cohort Study, living in Wales or Scotland at age seven whose parents consented to record linkage. We used height and weight measurements at age five to categorize children as obese (>98th centile) or overweight (>91st centile) (UK1990 clinical reference standards) and linked to hospital admissions, up to age 14 years, in the Patient Episode Database for Wales and Scottish Morbidity Records. Negative binomial regression models compared rates of inpatient admissions by weight status at age five. RESULTS:At age five, 11.5% and 6.7% of children were overweight or obese, respectively; 1221 (38%) children were subsequently admitted to hospital at least once. Admissions were not increased among children with overweight or obesity (adjusted rate ratio [RR], 95% confidence interval [CI]: 0.87, 0.68-1.10 and 1.16, 0.87-1.54, respectively). CONCLUSIONS:In this nationally representative cohort of children in Wales and Scotland, those with overweight or obesity at entry to primary school did not have increased rates of hospital admissions in later childhood and early adolescence."
+30729733,https://doi.org/10.1111/ijpo.12512,Predictors of objectively measured physical activity in 12-month-old infants: A study of linked birth cohort data with electronic health records.,"Raza H, Zhou SM, Todd C, Christian D, Marchant E, Morgan K, Khanom A, Hill R, Lyons RA, Brophy S.","The School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Department of Sport and Physical Activity, Edge Hill University, Ormskirk, UK.; Health Data Research UK, Swansea University, Swansea, UK.; DECIPHer, School of Social Sciences, Cardiff University, Cardiff, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Abertawe Bro Morgannwg University Health Board (ABM UHB), Port Talbot, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.",Pediatric obesity,2019,"BACKGROUND:Physical activity (PA) levels are associated with long-term health, and levels of PA when young are predictive of adult activity levels. OBJECTIVES:This study examines factors associated with PA levels in 12-month infants. METHOD:One hundred forty-one mother-infant pairs were recruited via a longitudinal birth cohort study (April 2010 to March 2013). The PA level was collected using accelerometers and linked to postnatal notes and electronic medical records via the Secure Anonymised Information Linkage databank. Univariable and multivariable linear regressions were used to examine the factors associated with PA levels. RESULTS:Using univariable analysis, higher PA was associated with the following (P value less than 0.05): being male, larger infant size, healthy maternal blood pressure levels, full-term gestation period, higher consumption of vegetables (infant), lower consumption of juice (infant), low consumption of adult crisps (infant), longer breastfeeding duration, and more movement during sleep (infant) but fewer night wakings. Combined into a multivariable regression model (R2  = 0.654), all factors remained significant, showing lower PA levels were associated with female gender, smaller infant, preterm birth, higher maternal blood pressure, low vegetable consumption, high crisp consumption, and less night movement. CONCLUSION:The PA levels of infants were strongly associated with both gestational and postnatal environmental factors. Healthy behaviours appear to cluster, and a healthy diet was associated with a more active infant. Boys were substantially more active than girls, even at age 12 months. These findings can help inform interventions to promote healthier lives for infants and to understand the determinants of their PA levels."
 31113941,https://doi.org/10.1038/s41467-019-10417-4,Author Correction: Towards a data-integrated cell.,"Malod-Dognin N, Petschnigg J, Windels SFL, Povh J, Hemingway H, Ketteler R, Pržulj N.","Department of Computer Science, University College London, London, WC1E 6BT, UK.; Department of Computer Science, University College London, London, WC1E 6BT, UK.; Department of Computer Science, University College London, London, WC1E 6BT, UK.; Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana, 1000, Slovenia.; Health Data Research UK London, University College London, London, WC1E 6BT, UK.; MRC Laboratory for Molecular Cell Biology, University College London, London, WC1E 6BT, UK.; Department of Computer Science, University College London, London, WC1E 6BT, UK. natasa@cs.ucl.ac.uk.",Nature communications,2019,"The original version of this Article contained an error in the spelling of the author Harry Hemingway, which was incorrectly given as Harry Hemmingway. This has been corrected in both the PDF and HTML versions of the Article."
 31040096,https://doi.org/10.1016/s2352-4642(19)30114-2,"Antimicrobial-impregnated central venous catheters for prevention of neonatal bloodstream infection (PREVAIL): an open-label, parallel-group, pragmatic, randomised controlled trial.","Gilbert R, Brown M, Rainford N, Donohue C, Fraser C, Sinha A, Dorling J, Gray J, McGuire W, Gamble C, Oddie SJ, PREVAIL trial team.","UCL Great Ormond Street Institute of Child Health, London, UK; Health Data Research UK, London, UK. Electronic address: r.gilbert@ucl.ac.uk.; Clinical Trials Research Centre, Department of Biostatistics, University of Liverpool, Liverpool, UK.; Clinical Trials Research Centre, Department of Biostatistics, University of Liverpool, Liverpool, UK.; Clinical Trials Research Centre, Department of Biostatistics, University of Liverpool, Liverpool, UK.; UCL Great Ormond Street Institute of Child Health, London, UK.; Barts Health NHS Trust, London, UK; Blizard Institute, Queen Mary University of London, London, UK.; Division of Neonatal-Perinatal Medicine, Dalhousie University IWK Health Centre, Halifax, NS, Canada.; Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK.; Centre for Reviews and Dissemination, University of York, York, UK.; Clinical Trials Research Centre, Department of Biostatistics, University of Liverpool, Liverpool, UK.; Centre for Reviews and Dissemination, University of York, York, UK; Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK.",The Lancet. Child & adolescent health,2019,"BACKGROUND:Bloodstream infection is associated with high mortality and serious morbidity in preterm babies. Evidence from clinical trials shows that antimicrobial-impregnated central venous catheters (CVCs) reduce catheter-related bloodstream infection in adults and children receiving intensive care, but there is a paucity of similar evidence for babies receiving neonatal intensive care. METHODS:This open-label, parallel-group, pragmatic, randomised controlled trial was done in 18 neonatal intensive care units in England. Newborn babies who needed a peripherally inserted CVC (PICC) were allocated randomly (1:1) to receive either a PICC impregnated with miconazole and rifampicin or a standard (non-antimicrobial-impregnated) PICC. Random allocation was done with a web-based program, which was centrally controlled to ensure allocation concealment. Randomisation sequences were computer-generated in random blocks of two and four, and stratified by site. Masking of clinicians to PICC allocation was impractical because rifampicin caused brown staining of the antimicrobial-impregnated PICC. However, participant inclusion in analyses and occurrence of outcome events were determined following an analysis plan that was specified before individuals saw the unblinded data. The primary outcome was the time from random allocation to first microbiologically confirmed bloodstream or cerebrospinal fluid (CSF) infection between 24 h after randomisation and 48 h after PICC removal or death. We analysed outcome data according to the intention-to-treat principle. We excluded babies for whom a PICC was not inserted from safety analyses, as these analyses were done with groups defined by the PICC used. This trial is registered with ISRCTN, number 81931394. FINDINGS:Between Aug 12, 2015, and Jan 11, 2017, we randomly assigned 861 babies (754 [88%] born before 32 weeks of gestation) to receive an antimicrobial-impregnated PICC (430 babies) or standard PICC (431 babies). The median time to PICC removal was 8·20 days (IQR 4·77-12·13) in the antimicrobial-impregnated PICC group versus 7·86 days (5·00-12·53) days in the standard PICC group (hazard ratio [HR] 1·03, 95% CI 0·89-1·18, p=0·73), with 46 (11%) of 430 babies versus 44 (10%) of 431 babies having a microbiologically confirmed bloodstream or CSF infection. The time from random allocation to first bloodstream or CSF infection was similar between the two groups (HR 1·11, 95% CI 0·73-1·67, p=0·63). Secondary outcomes relating to infection, rifampicin resistance in positive blood or CSF cultures, mortality, clinical outcomes at neonatal unit discharge, and time to PICC removal were similar between the two groups, although rifampicin resistance in positive cultures of PICC tips was higher in the antimicrobial-impregnated PICC group (relative risk 3·51, 95% CI 1·16-10·57, p=0·018). 60 adverse events were reported from 49 (13%) patients in the antimicrobial-impregnated PICC group and 50 events from 45 (10%) babies in the standard PICC group. INTERPRETATION:We found no evidence of benefit or harm associated with miconazole and rifampicin-impregnated PICCs compared with standard PICCs for newborn babies. Future research should focus on other types of antimicrobial impregnation of PICCs and alternative approaches for preventing infection. FUNDING:UK National Institute for Health Research Health Technology Assessment programme."
 30102210,https://doi.org/10.1016/s1470-2045(18)30425-x,A roadmap for restoring trust in Big Data.,"Lawler M, Morris AD, Sullivan R, Birney E, Middleton A, Makaroff L, Knoppers BM, Horgan D, Eggermont A.","Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast BT9 7BL, UK; European Alliance for Personalised Medicine, Brussels, Belgium; Global Alliance for Genomics and Health, Boston, MA, USA; Health Data Research UK, London, UK. Electronic address: mark.lawler@qub.ac.uk.; Health Data Research UK, London, UK.; Institute for Cancer Policy, Kings College London, London, UK.; Global Alliance for Genomics and Health, Boston, MA, USA; European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK.; Global Alliance for Genomics and Health, Boston, MA, USA; Welcome Genome Campus, Society and Ethics Research, Cambridge, UK.; European Cancer Patient Coalition, Brussels, Belgium; University of Leuven, Leuven, Belgium.; Global Alliance for Genomics and Health, Boston, MA, USA; Centre for Genomics and Policy, McGill University, Montreal, QC, Canada.; European Alliance for Personalised Medicine, Brussels, Belgium.; European Alliance for Personalised Medicine, Brussels, Belgium; Gustave Roussy Cancer Campus Grand Paris, Villejuif, France.",The Lancet. Oncology,2018,
 30928767,https://doi.org/10.1016/j.evalprogplan.2019.03.002,Understanding the factors that influence health promotion evaluation: The development and validation of the evaluation practice analysis survey.,"Schwarzman J, Bauman A, Gabbe BJ, Rissel C, Shilton T, Smith BJ.","School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC, 3004, Australia. Electronic address: joanna.schwarzman@monash.edu.; Prevention Research Collaboration, School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia.; School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC, 3004, Australia; Health Data Research UK, Swansea UniversityMedical School, Swansea University, Singleton Park, Swansea, SA2 8PP, Wales, UK.; Prevention Research Collaboration, School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia.; National Heart Foundation of Australia, 334 Rokeby Road, Subiaco, WA 6008, Australia.; School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC, 3004, Australia; Prevention Research Collaboration, School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia.",Evaluation and program planning,2019,"The demand for improved quality of health promotion evaluation and greater capacity to undertake evaluation is growing, yet evidence of the challenges and facilitators to evaluation practice within the health promotion field is lacking. A limited number of evaluation capacity measurement instruments have been validated in government or non-government organisations (NGO), however there is no instrument designed for health promotion organisations. This study aimed to develop and validate an Evaluation Practice Analysis Survey (EPAS) to examine evaluation practices in health promotion organisations. Qualitative interviews, existing frameworks and instruments informed the survey development. Health promotion practitioners from government agencies and NGOs completed the survey (n = 169). Principal components analysis was used to determine scale structure and Cronbach's α used to estimate internal reliability. Logistic regression was conducted to assess predictive validity of selected EPAS scale. The final survey instrument included 25 scales (125 items). The EPAS demonstrated good internal reliability (α > 0.7) for 23 scales. Dedicated resources and time for evaluation, leadership, organisational culture and internal support for evaluation showed promising predictive validity. The EPAS can be used to describe elements of evaluation capacity at the individual, organisational and system levels and to guide initiatives to improve evaluation practice in health promotion organisations."
 30778056,https://doi.org/10.1038/s41467-019-08797-8,Towards a data-integrated cell.,"Malod-Dognin N, Petschnigg J, Windels SFL, Povh J, Hemingway H, Ketteler R, Pržulj N.","Department of Computer Science, University College London, London, WC1E 6BT, UK.; Department of Computer Science, University College London, London, WC1E 6BT, UK.; Department of Computer Science, University College London, London, WC1E 6BT, UK.; Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana, 1000, Slovenia.; Health Data Research UK London, University College London, London, WC1E 6BT, UK.; MRC Laboratory for Molecular Cell Biology, University College London, London, WC1E 6BT, UK.; Department of Computer Science, University College London, London, WC1E 6BT, UK. natasa@cs.ucl.ac.uk.",Nature communications,2019,"We are increasingly accumulating molecular data about a cell. The challenge is how to integrate them within a unified conceptual and computational framework enabling new discoveries. Hence, we propose a novel, data-driven concept of an integrated cell, iCell. Also, we introduce a computational prototype of an iCell, which integrates three omics, tissue-specific molecular interaction network types. We construct iCells of four cancers and the corresponding tissue controls and identify the most rewired genes in cancer. Many of them are of unknown function and cannot be identified as different in cancer in any specific molecular network. We biologically validate that they have a role in cancer by knockdown experiments followed by cell viability assays. We find additional support through Kaplan-Meier survival curves of thousands of patients. Finally, we extend this analysis to uncover pan-cancer genes. Our methodology is universal and enables integrative comparisons of diverse omics data over cells and tissues."
 30727941,https://doi.org/10.1186/s12859-019-2633-8,DeepPVP: phenotype-based prioritization of causative variants using deep learning.,"Boudellioua I, Kulmanov M, Schofield PN, Gkoutos GV, Hoehndorf R.","Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia.; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia.; Department of Physiology, Development & Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK.; College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, B15 2TT, UK.; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia. robert.hoehndorf@kaust.edu.sa.",BMC bioinformatics,2019,"BACKGROUND:Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In these methods, pathogenicity prediction is combined with a semantic similarity measure to prioritize not only variants that are likely to be dysfunctional but those that are likely involved in the pathogenesis of a patient's phenotype. RESULTS:We have developed DeepPVP, a variant prioritization method that combined automated inference with deep neural networks to identify the likely causative variants in whole exome or whole genome sequence data. We demonstrate that DeepPVP performs significantly better than existing methods, including phenotype-based methods that use similar features. DeepPVP is freely available at https://github.com/bio-ontology-research-group/phenomenet-vp . CONCLUSIONS:DeepPVP further improves on existing variant prioritization methods both in terms of speed as well as accuracy."
+30659777,https://doi.org/10.1111/ijpo.12505,Are children with clinical obesity at increased risk of inpatient hospital admissions? An analysis using linked electronic health records in the UK millennium cohort study.,"Griffiths LJ, Cortina-Borja M, Bandyopadhyay A, Tingay K, De Stavola BL, Bedford H, Akbari A, Firman N, Lyons RA, Dezateux C.","Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; National Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, UK.; Administrative Data Research Centre Wales, Swansea University Medical School, Swansea, UK.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.",Pediatric obesity,2019,"BACKGROUND:Few studies have examined health service utilization of children with overweight or obesity by using linked electronic health records (EHRs). OBJECTIVE/METHODS:We analysed EHRs from 3269 children (1678 boys; 51.3% [weighted]) participating in the Millennium Cohort Study, living in Wales or Scotland at age seven whose parents consented to record linkage. We used height and weight measurements at age five to categorize children as obese (>98th centile) or overweight (>91st centile) (UK1990 clinical reference standards) and linked to hospital admissions, up to age 14 years, in the Patient Episode Database for Wales and Scottish Morbidity Records. Negative binomial regression models compared rates of inpatient admissions by weight status at age five. RESULTS:At age five, 11.5% and 6.7% of children were overweight or obese, respectively; 1221 (38%) children were subsequently admitted to hospital at least once. Admissions were not increased among children with overweight or obesity (adjusted rate ratio [RR], 95% confidence interval [CI]: 0.87, 0.68-1.10 and 1.16, 0.87-1.54, respectively). CONCLUSIONS:In this nationally representative cohort of children in Wales and Scotland, those with overweight or obesity at entry to primary school did not have increased rates of hospital admissions in later childhood and early adolescence."
+31204027,https://doi.org/10.1016/j.injury.2019.06.012,"Comparing the outcomes of isolated, serious traumatic brain injury in older adults managed at major trauma centres and neurosurgical services: A registry-based cohort study.","Dunn MS, Beck B, Simpson PM, Cameron PA, Kennedy M, Maiden M, Judson R, Gabbe BJ.","Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia. Electronic address: matthew.dunn@monash.edu.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; Emergency and Trauma Centre, The Alfred Hospital, Melbourne, Victoria, Australia.; Adult Retrieval Victoria, Ambulance Victoria, Melbourne, Victoria, Australia.; Department of Intensive Care, Geelong University Hospital, Geelong, Australia; Department of Intensive Care, Royal Adelaide Hospital, Adelaide, Australia.; Department of General Surgery, The Royal Melbourne Hospital, Melbourne, Victoria, Australia; Department of Surgery, The University of Melbourne, Melbourne, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; Health Data Research UK, Swansea University Medical School, Swansea University, Swansea, United Kingdom.",Injury,2019,"BACKGROUND:The incidence of older adult traumatic brain injury (TBI) is increasing in both high and middle to low-income countries. It is unknown whether older adults with isolated, serious TBI can be safely managed outside of major trauma centres. This registry based cohort study aimed to compare mortality and functional outcomes of older adults with isolated, serious TBI who were managed at specialised Major Trauma Services (MTS) and Metropolitan Neurosurgical Services (MNS). METHOD:Older adults (65 years and over) who sustained an isolated, serious TBI following a low fall (from standing or ≤ 1 m) were extracted from the Victorian State Trauma Registry from 2007 to 2016. Multivariable models were fitted to assess the association between hospital designation (MTS vs. MNS) and the two outcomes of interest: in-hospital mortality and functional outcome, adjusting for potential confounders. Functional outcomes were measured using the Glasgow Outcome Scale Extended at six months post-injury. RESULTS:From 2007-2016, there were 1904 older adults who sustained an isolated, serious TBI from a low fall who received definitive care at an MTS (n = 1124) or an MNS (n = 780). After adjusting for confounders, there was no mortality benefit for patients managed at an MTS over an MNS (OR = 0.84; 95% CI: 0.65, 1.08; P = 0.17) or improvement in functional outcome six months post-injury (OR = 1.13; 95% CI: 0.94, 1.36; P = 0.21). CONCLUSION:For older adults with isolated, serious TBI following a low fall, there was no difference in mortality or functional outcome based on definitive management at an MTS or an MNS. This confirms that MNS without the added designation of a major trauma centre are a suitable destination for the management of isolated, serious TBI in older adults."
 30183734,https://doi.org/10.1371/journal.pone.0202359,Time spent at blood pressure target and the risk of death and cardiovascular diseases.,"Chung SC, Pujades-Rodriguez M, Duyx B, Denaxas SC, Pasea L, Hingorani A, Timmis A, Williams B, Hemingway H.","Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Institute of Cardiovascular Science, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.",PloS one,2018,"BACKGROUND:The time a patient spends with blood pressure at target level is an intuitive measure of successful BP management, but population studies on its effectiveness are as yet unavailable. METHOD:We identified a population-based cohort of 169,082 individuals with newly identified high blood pressure who were free of cardiovascular disease from January 1997 to March 2010. We used 1.64 million clinical blood pressure readings to calculate the TIme at TaRgEt (TITRE) based on current target blood pressure levels. RESULT:The median (Inter-quartile range) TITRE among all patients was 2.8 (0.3, 5.6) months per year, only 1077 (0.6%) patients had a TITRE ≥11 months. Compared to people with a 0% TITRE, patients with a TITRE of 3-5.9 months, and 6-8.9 months had 75% and 78% lower odds of the composite of cardiovascular death, myocardial infarction and stroke (adjusted odds ratios, 0.25 (95% confidence interval: 0.21, 0.31) and 0.22 (0.17, 0.27), respectively). These associations were consistent for heart failure and any cardiovascular disease and death (comparing a 3-5.9 month to 0% TITRE, 63% and 60% lower in odds, respectively), among people who did or did not have blood pressure 'controlled' on a single occasion during the first year of follow-up, and across groups defined by number of follow-up BP measure categories. CONCLUSION:Based on the current frequency of measurement of blood pressure this study suggests that few newly hypertensive patients sustained a complete, year-round on target blood pressure over time. The inverse associations between a higher TITRE and lower risk of incident cardiovascular diseases were independent of widely-used blood pressure 'control' indicators. Randomized trials are required to evaluate interventions to increase a person's time spent at blood pressure target."
 30981377,https://doi.org/10.1016/j.aap.2019.03.007,How much space do drivers provide when passing cyclists? Understanding the impact of motor vehicle and infrastructure characteristics on passing distance.,"Beck B, Chong D, Olivier J, Perkins M, Tsay A, Rushford A, Li L, Cameron P, Fry R, Johnson M.","Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia. Electronic address: ben.beck@monash.edu.; Faculty of Science, The University of Melbourne, Victoria, Australia.; School of Mathematics and Statistics, University of New South Wales, New South Wales, Australia; School of Aviation, Transport and Road Safety (TARS) Research Centre, University of New South Wales, Sydney, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia.; Faculty of Information Technology, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Emergency and Trauma Centre, The Alfred, Melbourne, Victoria, Australia; National Trauma Research Institute, Victoria, Australia.; Health Data Research UK, Swansea UniversityMedical School,Swansea University, UK.; Institute of Transport Studies, Faculty of Engineering, Monash University, Victoria Australia; Amy Gillett Foundation, Victoria, Australia.",Accident; analysis and prevention,2019,"BACKGROUND:Understanding factors that influence the distance that drivers provide when passing cyclists is critical to reducing subjective risk and improving cycling participation. This study aimed to quantify passing distance and assess the impact of motor vehicle and road infrastructure characteristics on passing distance. METHODS:An on-road observational study was conducted in Victoria, Australia. Participants had a custom device installed on their bicycle and rode as per their usual cycling for one to two weeks. A hierarchical linear model was used to investigate the relationship between motor vehicle and infrastructure characteristics (location, presence of on-road marked bicycle lane and the presence of parked cars on the kerbside) and passing distance (defined as the lateral distance between the end of the bicycle handlebars and the passing motor vehicle). RESULTS:Sixty cyclists recorded 18,527 passing events over 422 trips. The median passing distance was 173 cm (Q1: 137 cm, Q3: 224 cm) and 1085 (5.9%) passing events were less than 100 cm. Relative to sedans, 4WDs had a reduced mean passing distance of 15 cm (Q1: 12 cm, Q3: 17 cm) and buses had a reduced mean passing distance of 28 cm (Q1: 16 cm, Q3: 40 cm). Relative to passing events that occurred on roads without a marked bicycle lane and without parked cars, passing events on roads with a bike lane with no parked cars had a reduced mean passing distance of 27 cm (Q1: 25 cm, Q3: 29 cm), and passing events on roads with a bike lane and parked cars had a mean lower passing distance of 40 cm (Q1: 37 cm, Q3: 43 cm). CONCLUSIONS:One in every 17 passing events was a close (<100 cm) passing event. We identified that on-road bicycle lanes and parked cars reduced passing distance. These data can be used to inform the selection and design of cycling-related infrastructure and road use with the aim of improving safety for cyclists."
 30014898,https://doi.org/10.1016/j.envres.2018.07.015,Estimation of TETRA radio use in the Airwave Health Monitoring Study of the British police forces.,"Vergnaud AC, Aresu M, Kongsgård HW, McRobie D, Singh D, Spear J, Heard A, Gao H, Carpenter JR, Elliott P.","Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Faculty of Medicine, Norwegian University of Science and Technology (NTNU), Norway.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Medical Statistics Unit, London School of Hygiene and Tropical Medicine London, WC1E 7HT, United Kingdom.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom; Imperial College London NIHR Biomedical Research Centre, London, United Kingdom; Health Data Research UK-London, London, United Kingdom. Electronic address: p.elliott@imperial.ac.uk.",Environmental research,2018,"BACKGROUND:The Airwave Health Monitoring Study aims to investigate the possible long-term health effects of Terrestrial Trunked Radio (TETRA) use among the police forces in Great Britain. Here, we investigate whether objective data from the network operator could be used to correct for misreporting in self-reported data and expand the radio usage availability in our cohort. METHODS:We estimated average monthly usage of personal radio in the 12 months prior to enrolment from a missing value imputation model and evaluated its performance against objective and self-reported data. Factors associated with TETRA radio usage variables were investigated using Chi-square tests and analysis of variance. RESULTS:The imputed data were better correlated with objective than self-reported usage (Spearman correlation coefficient = 0.72 vs. 0. 52 and kappa 0.56 [95% confidence interval 0.55, 0.56] vs. 0.46 [0.45, 0.47]), although the imputation model tended to under-estimate use for higher users. Participants with higher personal radio usage were more likely to be younger, men vs. women and officer vs. staff. The median average monthly usage level for the entire cohort was estimated to be 29.3 min (95% CI: [7.2, 66.6]). CONCLUSION:The availability of objective personal radio records for a large proportion of users allowed us to develop a robust imputation model and hence obtain personal radio usage estimates for ~50,000 participants. This substantially reduced exposure misclassification compared to using self-reported data and will allow us to carry out analyses of TETRA usage for the entire cohort in future work."
-30949070,https://doi.org/10.3389/fpsyt.2019.00109,Real World Implementation of a Transdiagnostic Risk Calculator for the Automatic Detection of Individuals at Risk of Psychosis in Clinical Routine: Study Protocol.,"Fusar-Poli P, Oliver D, Spada G, Patel R, Stewart R, Dobson R, McGuire P.","Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.",Frontiers in psychiatry,2019,"Background: Primary indicated prevention in individuals at-risk for psychosis has the potential to improve the outcomes of this disorder. The ability to detect the majority of at-risk individuals is the main barrier toward extending benefits for the lives of many adolescents and young adults. Current detection strategies are highly inefficient. Only 5% (standalone specialized early detection services) to 12% (youth mental health services) of individuals who will develop a first psychotic disorder can be detected at the time of their at-risk stage. To overcome these challenges a pragmatic, clinically-based, individualized, transdiagnostic risk calculator has been developed to detect individuals at-risk of psychosis in secondary mental health care at scale. This calculator has been externally validated and has demonstrated good prognostic performance. However, it is not known whether it can be used in the real world clinical routine. For example, clinicians may not be willing to adhere to the recommendations made by the transdiagnostic risk calculator. Implementation studies are needed to address pragmatic challenges relating to the real world use of the transdiagnostic risk calculator. The aim of the current study is to provide in-vitro and in-vivo feasibility data to support the implementation of the transdiagnostic risk calculator in clinical routine. Method: This is a study which comprises of two subsequent phases: an in-vitro phase of 1 month and an in-vivo phase of 11 months. The in-vitro phase aims at developing and integrating the transdiagnostic risk calculator in the local electronic health register (primary outcome). The in-vivo phase aims at addressing the clinicians' adherence to the recommendations made by the transdiagnostic risk calculator (primary outcome) and other secondary feasibility parameters that are necessary to estimate the resources needed for its implementation. Discussion: This is the first implementation study for risk prediction models in individuals at-risk for psychosis. Ultimately, successful implementation is the true measure of a prediction model's utility. Therefore, the overall translational deliverable of the current study would be to extend the benefits of primary indicated prevention and improve outcomes of first episode psychosis. This may produce significant social benefits for many adolescents and young adults and their families."
 29944675,https://doi.org/10.1371/journal.pone.0199026,"The diagnosis, burden and prognosis of dementia: A record-linkage cohort study in England.","Pujades-Rodriguez M, Assi V, Gonzalez-Izquierdo A, Wilkinson T, Schnier C, Sudlow C, Hemingway H, Whiteley WN.","Leeds Institute of Health Sciences, University of Leeds, Leeds, United Kingdom.; Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom.; Institute of Health Informatics, University College London, London, United Kingdom.; Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom.; Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom.; Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom.; Institute of Health Informatics, University College London, London, United Kingdom.; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.",PloS one,2018,"OBJECTIVES:Electronic health records (EHR) might be a useful resource to study the risk factors and clinical care of people with dementia. We sought to determine the diagnostic validity of dementia captured in linked EHR. METHODS AND FINDINGS:A cohort of adults in linked primary care, hospital, disease registry and mortality records in England, [CALIBER (CArdiovascular disease research using LInked Bespoke studies and Electronic health Records)]. The proportion of individuals with dementia, Alzheimer's disease, vascular and rare dementia in each data source was determined. A comparison was made of symptoms and care between people with dementia and age-, sex- and general practice-matched controls, using conditional logistic regression. The lifetime risk and prevalence of dementia and mortality rates in people with and without dementia were estimated with random-effects Poisson models. There were 47,386 people with dementia: 12,633 with Alzheimer's disease, 9540 with vascular and 1539 with rare dementia. Seventy-four percent of cases had corroborating evidence of dementia. People with dementia were more likely to live in a deprived area (conditional OR 1.26;95%CI:1.20-1.31 most vs least deprived), have documented memory impairment (cOR = 11.97;95%CI:11.24-12.75), falls (cOR = 2.36;95%CI:2.31-2.41), depression (cOR = 2.03; 95%CI:1.98-2.09) or anxiety (cOR = 1.27; 95%CI:1.23-1.32). The lifetime risk of dementia at age 65 was 9.2% (95%CI:9.0%-9.4%), in men and 14.9% (95%CI:14.7%-15.1%) in women. The population prevalence of recorded dementia increased from 0.3% in 2000 to 0.7% in 2010. A higher mortality rate was observed in people with than without dementia (IRR = 1.56;95%CI:1.54-1.58). CONCLUSIONS:Most people with a record of dementia in linked UK EHR had some corroborating evidence for diagnosis. The estimated 10-year risk of dementia was higher than published population-based estimations. EHR are therefore a promising source of data for dementia research."
-30819382,https://doi.org/10.1016/j.jchf.2019.01.009,Adverse Drug Reactions to Guideline-Recommended Heart Failure Drugs in Women: A Systematic Review of the Literature.,"Bots SH, Groepenhoff F, Eikendal ALM, Tannenbaum C, Rochon PA, Regitz-Zagrosek V, Miller VM, Day D, Asselbergs FW, den Ruijter HM.","Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Laboratory of Clinical Chemistry and Haematology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Faculties of Pharmacy and Medicine, Université de Montréal, Montréal, Canada.; Women's College Research Institute, Women's College Hospital, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.; Institute for Gender in Medicine and Center for Cardiovascular Research, Charite, University Medicine Berlin, Berlin, Germany; DZHK (German Center for Cardiovascular Research), partner site Berlin, Berlin, Germany.; Women's Health Research Center, Mayo Clinic, Rochester, Minnesota.; UniQure, Amsterdam, the Netherlands.; Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; Institute of Cardiovascular Science, Faculty of Popular Health Sciences, University College London, London, United Kingdom; Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom.; Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands. Electronic address: h.m.denruijter-2@umcutrecht.nl.",JACC. Heart failure,2019,"OBJECTIVES:This study sought to summarize all available evidence on sex differences in adverse drug reactions (ADRs) to heart failure (HF) medication. BACKGROUND:Women are more likely to experience ADRs than men, and these reactions may negatively affect women's immediate and long-term health. HF in particular is associated with increased ADR risk because of the high number of comorbidities and older age. However, little is known about ADRs in women with HF who are treated with guideline-recommended drugs. METHODS:A systematic search of PubMed and EMBASE was performed to collect all available information on ADRs to angiotensin-converting enzyme inhibitors, β-blockers, angiotensin II receptor blockers, mineralocorticoid receptor antagonists, ivabradine, and digoxin in both women and men with HF. RESULTS:The search identified 155 eligible records, of which only 11 (7%) reported ADR data for women and men separately. Sex-stratified reporting of ADRs did not increase over the last decades. Six of the 11 studies did not report sex differences. Three studies reported a higher risk of angiotensin-converting enzyme inhibitor-related ADRs in women, 1 study showed higher digoxin-related mortality risk for women, and 1 study reported a higher risk of mineralocorticoid receptor antagonist-related ADRs in men. No sex differences in ADRs were reported for angiotensin II receptor blockers and β-blockers. Sex-stratified data were not available for ivabradine. CONCLUSIONS:These results underline the scarcity of ADR data stratified by sex. The study investigators call for a change in standard scientific practice toward reporting of ADR data for women and men separately."
+30949070,https://doi.org/10.3389/fpsyt.2019.00109,Real World Implementation of a Transdiagnostic Risk Calculator for the Automatic Detection of Individuals at Risk of Psychosis in Clinical Routine: Study Protocol.,"Fusar-Poli P, Oliver D, Spada G, Patel R, Stewart R, Dobson R, McGuire P.","Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.",Frontiers in Psychiatry,2019,"Background: Primary indicated prevention in individuals at-risk for psychosis has the potential to improve the outcomes of this disorder. The ability to detect the majority of at-risk individuals is the main barrier toward extending benefits for the lives of many adolescents and young adults. Current detection strategies are highly inefficient. Only 5% (standalone specialized early detection services) to 12% (youth mental health services) of individuals who will develop a first psychotic disorder can be detected at the time of their at-risk stage. To overcome these challenges a pragmatic, clinically-based, individualized, transdiagnostic risk calculator has been developed to detect individuals at-risk of psychosis in secondary mental health care at scale. This calculator has been externally validated and has demonstrated good prognostic performance. However, it is not known whether it can be used in the real world clinical routine. For example, clinicians may not be willing to adhere to the recommendations made by the transdiagnostic risk calculator. Implementation studies are needed to address pragmatic challenges relating to the real world use of the transdiagnostic risk calculator. The aim of the current study is to provide in-vitro and in-vivo feasibility data to support the implementation of the transdiagnostic risk calculator in clinical routine. Method: This is a study which comprises of two subsequent phases: an in-vitro phase of 1 month and an in-vivo phase of 11 months. The in-vitro phase aims at developing and integrating the transdiagnostic risk calculator in the local electronic health register (primary outcome). The in-vivo phase aims at addressing the clinicians' adherence to the recommendations made by the transdiagnostic risk calculator (primary outcome) and other secondary feasibility parameters that are necessary to estimate the resources needed for its implementation. Discussion: This is the first implementation study for risk prediction models in individuals at-risk for psychosis. Ultimately, successful implementation is the true measure of a prediction model's utility. Therefore, the overall translational deliverable of the current study would be to extend the benefits of primary indicated prevention and improve outcomes of first episode psychosis. This may produce significant social benefits for many adolescents and young adults and their families."
 30082368,https://doi.org/10.1136/bmjopen-2018-024755,Validating injury burden estimates using population birth cohorts and longitudinal cohort studies of injury outcomes: the VIBES-Junior study protocol.,"Gabbe BJ, Dipnall JF, Lynch JW, Rivara FP, Lyons RA, Ameratunga S, Brussoni M, Lecky FE, Bradley C, Simpson PM, Beck B, Demmler JC, Lyons J, Schneeberg A, Harrison JE.","School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; School of Public Health, University of Adelaide, Adelaide, South Australia, Australia.; Departments of Pediatrics and Epidemiology, and the Harborview Injury Prevention and Research Center, University of Washington, Seattle, Washington, USA.; Health Data Research UK, Swansea University, Swansea, UK.; School of Population Health, University of Auckland, Auckland, New Zealand.; Department of Pediatrics, School of Population and Public Health, University of British Columbia, Vancouver, Canada.; School of Health and Related Research, University of Sheffield, Sheffield, UK.; South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia.; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.; British Columbia Injury Research and Prevention Unit, Children's Hospital Research Institute, Vancouver, Canada.; Research Centre for Injury Studies, Flinders University, Adelaide, South Australia, Australia.",BMJ open,2018,"Traumatic injury is a leading contributor to the global disease burden in children and adolescents, but methods used to estimate burden do not account for differences in patterns of injury and recovery between children and adults. A lack of empirical data on postinjury disability in children has limited capacity to derive valid disability weights and describe the long-term individual and societal impacts of injury in the early part of life. The aim of this study is to establish valid estimates of the burden of non-fatal injury in children and adolescents.Five longitudinal studies of paediatric injury survivors <18 years at the time of injury (Australia, Canada, UK and USA) and two whole-of-population linked administrative data paediatric studies (Australia and Wales) will be analysed over a 3-year period commencing 2018. Meta-analysis of deidentified patient-level data (n≈2,600) from five injury-specific longitudinal studies (Victorian State Trauma Registry; Victorian Orthopaedic Trauma Outcomes Registry; UK Burden of Injury; British Columbia Children's Hospital Longitudinal Injury Outcomes; Children's Health After Injury) and >1 million children from two whole-of-population cohorts (South Australian Early Childhood Data Project and Wales Electronic Cohort for Children). Systematic analysis of pooled injury-specific cohort data using a variety of statistical techniques, and parallel analysis of whole-of-population cohorts, will be used to develop estimated disability weights for years lost due to disability, establish appropriate injury classifications and explore factors influencing recovery.The project was approved by the Monash University Human Research Ethics Committee project number 12 311. Results of this study will be submitted for publication in internationally peer-reviewed journals. The findings from this project have the capacity to improve the validity of paediatric injury burden measurements in future local and global burden of disease studies."
+30819382,https://doi.org/10.1016/j.jchf.2019.01.009,Adverse Drug Reactions to Guideline-Recommended Heart Failure Drugs in Women: A Systematic Review of the Literature.,"Bots SH, Groepenhoff F, Eikendal ALM, Tannenbaum C, Rochon PA, Regitz-Zagrosek V, Miller VM, Day D, Asselbergs FW, den Ruijter HM.","Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Laboratory of Clinical Chemistry and Haematology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Faculties of Pharmacy and Medicine, Université de Montréal, Montréal, Canada.; Women's College Research Institute, Women's College Hospital, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.; Institute for Gender in Medicine and Center for Cardiovascular Research, Charite, University Medicine Berlin, Berlin, Germany; DZHK (German Center for Cardiovascular Research), partner site Berlin, Berlin, Germany.; Women's Health Research Center, Mayo Clinic, Rochester, Minnesota.; UniQure, Amsterdam, the Netherlands.; Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; Institute of Cardiovascular Science, Faculty of Popular Health Sciences, University College London, London, United Kingdom; Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom.; Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands. Electronic address: h.m.denruijter-2@umcutrecht.nl.",JACC. Heart failure,2019,"OBJECTIVES:This study sought to summarize all available evidence on sex differences in adverse drug reactions (ADRs) to heart failure (HF) medication. BACKGROUND:Women are more likely to experience ADRs than men, and these reactions may negatively affect women's immediate and long-term health. HF in particular is associated with increased ADR risk because of the high number of comorbidities and older age. However, little is known about ADRs in women with HF who are treated with guideline-recommended drugs. METHODS:A systematic search of PubMed and EMBASE was performed to collect all available information on ADRs to angiotensin-converting enzyme inhibitors, β-blockers, angiotensin II receptor blockers, mineralocorticoid receptor antagonists, ivabradine, and digoxin in both women and men with HF. RESULTS:The search identified 155 eligible records, of which only 11 (7%) reported ADR data for women and men separately. Sex-stratified reporting of ADRs did not increase over the last decades. Six of the 11 studies did not report sex differences. Three studies reported a higher risk of angiotensin-converting enzyme inhibitor-related ADRs in women, 1 study showed higher digoxin-related mortality risk for women, and 1 study reported a higher risk of mineralocorticoid receptor antagonist-related ADRs in men. No sex differences in ADRs were reported for angiotensin II receptor blockers and β-blockers. Sex-stratified data were not available for ivabradine. CONCLUSIONS:These results underline the scarcity of ADR data stratified by sex. The study investigators call for a change in standard scientific practice toward reporting of ADR data for women and men separately."
 31063847,https://doi.org/10.1016/j.bbi.2019.05.009,Transcriptomic analysis of probable asymptomatic and symptomatic alzheimer brains.,"Patel H, Hodges AK, Curtis C, Lee SH, Troakes C, Dobson RJB, Newhouse SJ.","Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK.; Department of Old Age Psychiatry, Maurice Wohl Clinical Neuroscience Institute Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK.; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK; Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK.; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK; Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK.; Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK; London Neurodegenerative Diseases Brain Bank, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK.; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK; Health Data Research UK London, University College London, 222 Euston Road, London, UK; Institute of Health Informatics, University College London, 222 Euston Road, London, UK; The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, 222 Euston Road, London, UK. Electronic address: richard.j.dobson@kcl.ac.uk.; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK; Health Data Research UK London, University College London, 222 Euston Road, London, UK; Institute of Health Informatics, University College London, 222 Euston Road, London, UK; The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, 222 Euston Road, London, UK. Electronic address: stephen.newhouse@kcl.ac.uk.","Brain, behavior, and immunity",2019,"Individuals with intact cognition and neuropathology consistent with Alzheimer's disease (AD) are referred to as asymptomatic AD (AsymAD). These individuals are highly likely to develop AD, yet transcriptomic changes in the brain which might reveal mechanisms for their AD vulnerability are currently unknown. Entorhinal cortex, frontal cortex, temporal cortex and cerebellum tissue from 27 control, 33 AsymAD and 52 AD human brains were microarray expression profiled. Differential expression analysis identified a significant increase of transcriptomic activity in the frontal cortex of AsymAD subjects, suggesting fundamental changes in AD may initially begin within the frontal cortex region prior to AD diagnosis. Co-expression analysis identified an overactivation of the brain ""glutamate-glutamine cycle"", and disturbances in the brain energy pathways in both AsymAD and AD subjects, while the connectivity of key hub genes in this network indicates a shift from an already increased cell proliferation in AsymAD subjects to stress response and removal of amyloidogenic proteins in AD subjects. This study provides new insight into the earliest biological changes occurring in the brain prior to the manifestation of clinical AD symptoms and provides new potential therapeutic targets for early disease intervention."
+31220083,https://doi.org/10.1371/journal.pmed.1002833,Associations of genetically determined iron status across the phenome: A mendelian randomization study.,"Gill D, Benyamin B, Moore LSP, Monori G, Zhou A, Koskeridis F, Evangelou E, Laffan M, Walker AP, Tsilidis KK, Dehghan A, Elliott P, Hyppönen E, Tzoulaki I.","Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Australian Centre for Precision Health, University of South Australia, Adelaide, Australia.; National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Australian Centre for Precision Health, University of South Australia, Adelaide, Australia.; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Centre for Haematology, Imperial College London, United Kingdom.; Population Science & Experimental Medicine, Institute of Cardiovascular Science, University College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Australian Centre for Precision Health, University of South Australia, Adelaide, Australia.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.",PLoS medicine,2019,"BACKGROUND:Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status. METHODS AND FINDINGS:Genome-wide association study (GWAS) summary data obtained from 48,972 European individuals (55% female) across 19 cohorts in the Genetics of Iron Status Consortium were used to identify 3 genetic variants (rs1800562 and rs1799945 in the hemochromatosis gene [HFE] and rs855791 in the transmembrane protease serine 6 gene [TMPRSS6]) that associate with increased serum iron, ferritin, and transferrin saturation and decreased transferrin levels, thus serving as instruments for systemic iron status. Phenome-wide association study (PheWAS) of these instruments was performed on 424,439 European individuals (54% female) in the UK Biobank who were aged 40-69 years when recruited from 2006 to 2010, with their genetic data linked to Hospital Episode Statistics (HES) from April, 1995 to March, 2016. Two-sample summary data mendelian randomization (MR) analysis was performed to investigate the effect of varying iron status on outcomes across the human phenome. MR-PheWAS analysis for the 3 iron status genetic instruments was performed separately and then pooled by meta-analysis. Correction was made for testing of multiple correlated phenotypes using a 5% false discovery rate (FDR) threshold. Heterogeneity between MR estimates for different instruments was used to indicate possible bias due to effects of the genetic variants through pathways unrelated to iron status. There were 904 distinct phenotypes included in the MR-PheWAS analyses. After correcting for multiple testing, the 3 genetic instruments for systemic iron status demonstrated consistent evidence of a causal effect of higher iron status on decreasing risk of traits related to anemia (iron deficiency anemia: odds ratio [OR] scaled to a standard deviation [SD] increase in genetically determined serum iron levels 0.72, 95% confidence interval [CI] 0.64-0.81, P = 4 × 10-8) and hypercholesterolemia (hypercholesterolemia: OR 0.88, 95% CI 0.83-0.93, P = 2 × 10-5) and increasing risk of traits related to infection of the skin and related structures (cellulitis and abscess of the leg: OR 1.25, 95% CI 1.10-1.42, P = 6 × 10-4). The main limitations of this study relate to possible bias from pleiotropic effects of the considered genetic variants and misclassification of diagnoses in the HES data. Furthermore, this work only investigated participants with European ancestry, and the findings may not be applicable to other ethnic groups. CONCLUSIONS:Our findings offer novel, to our knowledge, insight into previously unreported effects of iron status, highlighting a potential protective effect of higher iron status on hypercholesterolemia and a detrimental role on risk of skin and skin structure infections. Given the modifiable and variable nature of iron status, these findings warrant further investigation."
 29780001,https://doi.org/10.1016/S2352-3026(18)30053-X,Automated typing of red blood cell and platelet antigens: a whole-genome sequencing study.,"Lane WJ, Westhoff CM, Gleadall NS, Aguad M, Smeland-Wagman R, Vege S, Simmons DP, Mah HH, Lebo MS, Walter K, Soranzo N, Di Angelantonio E, Danesh J, Roberts DJ, Watkins NA, Ouwehand WH, Butterworth AS, Kaufman RM, Rehm HL, Silberstein LE, Green RC, MedSeq Project.","Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA. Electronic address: wlane@bwh.harvard.edu.; New York Blood Center, New York, NY, USA.; Department of Haematology, University of Cambridge, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge, UK.; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.; New York Blood Center, New York, NY, USA.; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Laboratory for Molecular Medicine, Boston, MA, USA; Partners Personalized Medicine, Boston, MA, USA.; Wellcome Trust Sanger Institute, Hinxton, UK.; Department of Haematology, University of Cambridge, Cambridge, UK; Wellcome Trust Sanger Institute, Hinxton, UK; Cambridge Substantive Site, Health Data Research UK, Wellcome Genome Campus, Hinxton, UK.; Medical Research Council and British Heart Foundation Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK; National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK; Cambridge Substantive Site, Health Data Research UK, Wellcome Genome Campus, Hinxton, UK.; Medical Research Council and British Heart Foundation Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK; National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK; Department of Public Health and Primary Care, and British Heart Foundation Cambridge Centre of Excellence, Department of Medicine, University of Cambridge, Cambridge, UK; Wellcome Trust Sanger Institute, Hinxton, UK; Cambridge Substantive Site, Health Data Research UK, Wellcome Genome Campus, Hinxton, UK.; National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK; NHS Blood and Transplant-Oxford Centre, Oxford, UK; Biomedical Research Centre Haematology Theme and Radcliffe Department of Medicine, University of Oxford, Oxford, UK.; National Health Service (NHS) Blood and Transplant, Cambridge, UK.; Department of Haematology, University of Cambridge, Cambridge, UK; Department of Public Health and Primary Care, and British Heart Foundation Cambridge Centre of Excellence, Department of Medicine, University of Cambridge, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge, UK; NHS Blood and Transplant-Oxford Centre, Oxford, UK.; Medical Research Council and British Heart Foundation Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK; National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK; Cambridge Substantive Site, Health Data Research UK, Wellcome Genome Campus, Hinxton, UK.; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.; Harvard Medical School, Boston, MA, USA; Laboratory for Molecular Medicine, Boston, MA, USA; Partners Personalized Medicine, Boston, MA, USA; Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Broad Institute of Massachusetts Institute of Technology and Harvard, Boston, MA, USA.; Division of Transfusion Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.; Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Partners Personalized Medicine, Boston, MA, USA; Broad Institute of Massachusetts Institute of Technology and Harvard, Boston, MA, USA.",The Lancet. Haematology,2018,"BACKGROUND:There are more than 300 known red blood cell (RBC) antigens and 33 platelet antigens that differ between individuals. Sensitisation to antigens is a serious complication that can occur in prenatal medicine and after blood transfusion, particularly for patients who require multiple transfusions. Although pre-transfusion compatibility testing largely relies on serological methods, reagents are not available for many antigens. Methods based on single-nucleotide polymorphism (SNP) arrays have been used, but typing for ABO and Rh-the most important blood groups-cannot be done with SNP typing alone. We aimed to develop a novel method based on whole-genome sequencing to identify RBC and platelet antigens. METHODS:This whole-genome sequencing study is a subanalysis of data from patients in the whole-genome sequencing arm of the MedSeq Project randomised controlled trial (NCT01736566) with no measured patient outcomes. We created a database of molecular changes in RBC and platelet antigens and developed an automated antigen-typing algorithm based on whole-genome sequencing (bloodTyper). This algorithm was iteratively improved to address cis-trans haplotype ambiguities and homologous gene alignments. Whole-genome sequencing data from 110 MedSeq participants (30 × depth) were used to initially validate bloodTyper through comparison with conventional serology and SNP methods for typing of 38 RBC antigens in 12 blood-group systems and 22 human platelet antigens. bloodTyper was further validated with whole-genome sequencing data from 200 INTERVAL trial participants (15 × depth) with serological comparisons. FINDINGS:We iteratively improved bloodTyper by comparing its typing results with conventional serological and SNP typing in three rounds of testing. The initial whole-genome sequencing typing algorithm was 99·5% concordant across the first 20 MedSeq genomes. Addressing discordances led to development of an improved algorithm that was 99·8% concordant for the remaining 90 MedSeq genomes. Additional modifications led to the final algorithm, which was 99·2% concordant across 200 INTERVAL genomes (or 99·9% after adjustment for the lower depth of coverage). INTERPRETATION:By enabling more precise antigen-matching of patients with blood donors, antigen typing based on whole-genome sequencing provides a novel approach to improve transfusion outcomes with the potential to transform the practice of transfusion medicine. FUNDING:National Human Genome Research Institute, Doris Duke Charitable Foundation, National Health Service Blood and Transplant, National Institute for Health Research, and Wellcome Trust."
-31013802,https://doi.org/10.3390/ijerph16081325,Using Patient-Reported Outcomes to Predict Revision Arthroplasty Following Femoral Neck Fracture: Enhancing the Value of Clinical Registries through Data Linkage.,"Ekegren CL, de Steiger R, Edwards ER, Page RS, Hau R, Liew S, Oppy A, Gabbe BJ.","Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. christina.ekegren@monash.edu.; Epworth Hospital, Richmond, VIC 3121, Australia. richard.desteiger@epworth.org.au.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. ere@bigpond.net.au.; Department of Orthopaedics, University Hospital Geelong, Geelong, VIC 3220, Australia. richard.page@deakin.edu.au.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. raphaelhau@hotmail.com.; Department of Orthopaedic Surgery, Alfred Hospital, Melbourne, VIC 3004, Australia. s.liew@alfred.org.au.; Epworth Hospital, Richmond, VIC 3121, Australia. andrewoppy@me.com.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. belinda.gabbe@monash.edu.",International Journal of Environmental Research and Public Health,2019,"The aim of this study was to determine the association between patient-reported outcome measures (PROMs) six months following femoral neck fracture after a low fall and future arthroplasty, and the factors associated with this. Six-month post-fracture PROMs were collected from the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR) for patients aged >55 years who were admitted for a femoral neck fracture after a low fall between March 2007 and June 2015. These cases were linked with those registered by Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) up to October 2016. Multivariable analysis was performed using a Cox proportional hazards model to determine factors associated with future arthroplasty, including six-month PROMs. Of the 7077 hip fracture patients registered by VOTOR during the study period, 2325 met the inclusion criteria. Internal fixation being used for the initial hip fracture surgery, being younger and having no pre-injury disability were all independently associated with future revision or conversion to arthroplasty. Out of all PROMs, reporting pain and discomfort six months post-fracture was associated with a 9.5-fold increase in the risk of future arthroplasty (95% CI: 3.81, 23.67). The value of clinical registries can be enhanced via data linkage, in this case by using PROMs to predict arthroplasty following femoral neck fracture."
+31013802,https://doi.org/10.3390/ijerph16081325,Using Patient-Reported Outcomes to Predict Revision Arthroplasty Following Femoral Neck Fracture: Enhancing the Value of Clinical Registries through Data Linkage.,"Ekegren CL, de Steiger R, Edwards ER, Page RS, Hau R, Liew S, Oppy A, Gabbe BJ.","Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. christina.ekegren@monash.edu.; Epworth Hospital, Richmond, VIC 3121, Australia. richard.desteiger@epworth.org.au.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. ere@bigpond.net.au.; Department of Orthopaedics, University Hospital Geelong, Geelong, VIC 3220, Australia. richard.page@deakin.edu.au.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. raphaelhau@hotmail.com.; Department of Orthopaedic Surgery, Alfred Hospital, Melbourne, VIC 3004, Australia. s.liew@alfred.org.au.; Epworth Hospital, Richmond, VIC 3121, Australia. andrewoppy@me.com.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. belinda.gabbe@monash.edu.",International journal of environmental research and public health,2019,"The aim of this study was to determine the association between patient-reported outcome measures (PROMs) six months following femoral neck fracture after a low fall and future arthroplasty, and the factors associated with this. Six-month post-fracture PROMs were collected from the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR) for patients aged >55 years who were admitted for a femoral neck fracture after a low fall between March 2007 and June 2015. These cases were linked with those registered by Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) up to October 2016. Multivariable analysis was performed using a Cox proportional hazards model to determine factors associated with future arthroplasty, including six-month PROMs. Of the 7077 hip fracture patients registered by VOTOR during the study period, 2325 met the inclusion criteria. Internal fixation being used for the initial hip fracture surgery, being younger and having no pre-injury disability were all independently associated with future revision or conversion to arthroplasty. Out of all PROMs, reporting pain and discomfort six months post-fracture was associated with a 9.5-fold increase in the risk of future arthroplasty (95% CI: 3.81, 23.67). The value of clinical registries can be enhanced via data linkage, in this case by using PROMs to predict arthroplasty following femoral neck fracture."
+31234639,https://doi.org/10.1161/circulationaha.118.038814,Use of Genetic Variants Related to Antihypertensive Drugs to Inform on Efficacy and Side Effects.,"Gill D, Georgakis MK, Koskeridis F, Jiang L, Feng Q, Wei WQ, Theodoratou E, Elliott P, Denny JC, Malik R, Evangelou E, Dehghan A, Dichgans M, Tzoulaki I.","Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom.; Institute for Stroke and Dementia Research, University Hospital, and Graduate School for Systemic Neurosciences, Ludwig-Maximilians-Universität LMU, Munich, Germany.; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Greece.; Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN.; Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN.; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.; Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom; Medical Research Council-Public Health England Centre for Environment, School of Public Health, Imperial College London, United Kingdom; Imperial Biomedical Research Centre, Imperial College London and Imperial College NHS Healthcare Trust, United Kingdom; UK Dementia Research Institute at Imperial College London, United Kingdom; Health Data Research UK-London, United Kingdom.; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.; Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität LMU, Munich, Germany.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Greece.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom; Medical Research Council-Public Health England Centre for Environment, School of Public Health, Imperial College London, United Kingdom; UK Dementia Research Institute at Imperial College London, United Kingdom.; Institute for Stroke and Dementia Research, University Hospital, Ludwig-MaximiliansUniversität LMU, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Germany; German Center for Neurodegenerative Diseases (DZNE, Munich), Germany.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Greece; Medical Research Council-Public Health England Centre for Environment, School of Public Health, Imperial College London, United Kingdom; UK Dementia Research Institute at Imperial College London, United Kingdom.",Circulation,2019,"BACKGROUND:Drug effects can be investigated through natural variation in the genes for their protein targets. The present study aimed to use this approach to explore the potential side effects and repurposing potential of antihypertensive drugs, which are among the most commonly used medications worldwide. METHODS:Genetic proxies for the effect of antihypertensive drug classes were identified as variants in the genes for the corresponding targets that associated with systolic blood pressure at genome-wide significance. Mendelian randomization estimates for drug effects on coronary heart disease and stroke risk were compared with randomized, controlled trial results. Phenome-wide association study in the UK Biobank was performed to identify potential side effects and repurposing opportunities, with findings investigated in the Vanderbilt University biobank (BioVU) and in observational analysis of the UK Biobank. RESULTS:Suitable genetic proxies for angiotensin-converting enzyme inhibitors, β-blockers, and calcium channel blockers (CCBs) were identified. Mendelian randomization estimates for their effect on coronary heart disease and stroke risk, respectively, were comparable to results from randomized, controlled trials against placebo. A phenome-wide association study in the UK Biobank identified an association of the CCB standardized genetic risk score with increased risk of diverticulosis (odds ratio, 1.02 per standard deviation increase; 95% CI, 1.01-1.04), with a consistent estimate found in BioVU (odds ratio, 1.01; 95% CI, 1.00-1.02). Cox regression analysis of drug use in the UK Biobank suggested that this association was specific to nondihydropyridine CCBs (hazard ratio 1.49 considering thiazide diuretic agents as a comparator; 95% CI, 1.04-2.14) but not dihydropyridine CCBs (hazard ratio, 1.04; 95% CI, 0.83-1.32). CONCLUSIONS:Genetic variants can be used to explore the efficacy and side effects of antihypertensive medications. The identified potential effect of nondihydropyridine CCBs on diverticulosis risk could have clinical implications and warrants further investigation."
+31226389,https://doi.org/10.1016/j.jhep.2019.05.032,Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration.,"Wilman HR, Parisinos CA, Atabaki-Pasdar N, Kelly M, Louise Thomas E, Neubauer S, IMI DIRECT Consortium.","Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, U.K. and Perspectum Diagnostics Ltd., Oxford, UK. Electronic address: h.wilman@westminster.ac.uk.; Institute of Health Informatics, Faculty of Population Health Sciences, University College London, London, UK. Electronic address: c.parisinos@ucl.ac.uk.; Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, Malmö, Sweden. Electronic address: naimeh.atabaki_pasdar@med.lu.se.; Perspectum Diagnostics Ltd., Oxford, UK. Electronic address: matt.kelly@perspectum-diagnostics.com.; Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK. Electronic address: l.thomas3@westminster.ac.uk.; Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK and Perspectum Diagnostics Ltd., Oxford, UK. Electronic address: stefan.neubauer@perspectum.com.",Journal of hepatology,2019,"BACKGROUND & AIMS:Excess liver iron content is common and is linked to hepatic and extrahepatic disease risk. We aimed to identify genetic variants influencing liver iron content and use genetics to understand its link to other traits and diseases. METHODS:First, we performed a genome-wide association study (GWAS) in 8,289 individuals in UK Biobank with MRI quantified liver iron, and validated our findings in an independent cohort (n=1,513 from IMI DIRECT). Second, we used Mendelian randomisation to test the causal effects of 29 predominantly metabolic traits on liver iron content. Third, we tested phenome-wide associations between liver iron variants and 770 anthropometric traits and diseases. RESULTS:We identified three independent genetic variants (rs1800562 (C282Y) and rs1799945 (H63D) in HFE and rs855791 (V736A) in TMPRSS6) associated with liver iron content that reached the GWAS significance threshold (p < 5x10-8). The two HFE variants account for ∼85% of all cases of hereditary haemochromatosis. Mendelian randomisation analysis provided evidence that higher central obesity plays a causal role in increased liver iron content. Phenome-wide association analysis demonstrated shared aetiopathogenic mechanisms for elevated liver iron, high blood pressure, cirrhosis, malignancies, neuropsychiatric and rheumatological conditions, while also highlighting inverse associations with anaemias, lipidaemias and ischaemic heart disease. CONCLUSION:Our study provides genetic evidence that mechanisms underlying higher liver iron content are likely systemic rather than organ specific, that higher central obesity is causally associated with higher liver iron, and that liver iron shares common aetiology with multiple metabolic and non-metabolic diseases. LAY SUMMARY:Excess liver iron content is common and is associated with liver diseases and metabolic diseases including diabetes, high blood pressure, and heart disease. We find that three genetic variants are linked to increased risk of developing higher liver iron content. We show that the same genetic variants are linked to higher risk of many diseases, but they may also be associated with some health advantages. Finally, we use genetic variants associated with waist-to-hip ratio as a tool to show that central obesity is causally associated with increased liver iron content."
 30497795,https://doi.org/10.1016/S0140-6736(18)32207-4,Changes in health in the countries of the UK and 150 English Local Authority areas 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.,"Steel N, Ford JA, Newton JN, Davis ACJ, Vos T, Naghavi M, Glenn S, Hughes A, Dalton AM, Stockton D, Humphreys C, Dallat M, Schmidt J, Flowers J, Fox S, Abubakar I, Aldridge RW, Baker A, Brayne C, Brugha T, Capewell S, Car J, Cooper C, Ezzati M, Fitzpatrick J, Greaves F, Hay R, Hay S, Kee F, Larson HJ, Lyons RA, Majeed A, McKee M, Rawaf S, Rutter H, Saxena S, Sheikh A, Smeeth L, Viner RM, Vollset SE, Williams HC, Wolfe C, Woolf A, Murray CJL.","University of East Anglia, Norwich, UK. Electronic address: n.steel@uea.ac.uk.; University of East Anglia, Norwich, UK.; Public Health England, London, UK.; AD CAVE Solutions Ltd, London, UK; Imperial College London, London, UK.; Institute for Health Metrics and Evaluation, Seattle, WA, USA.; Institute for Health Metrics and Evaluation, Seattle, WA, USA.; Institute for Health Metrics and Evaluation, Seattle, WA, USA.; Public Health England, Oxford, UK.; University of East Anglia, Norwich, UK.; NHS Health Scotland, Edinburgh, UK.; Public Health Wales, Carmarthen, UK.; Public Health Agency, Belfast, UK.; Public Health England, London, UK.; Public Health England, London, UK.; Public Health England, London, UK.; University College London, London, UK.; University College London, London, UK.; Public Health England, London, UK.; Cambridge Institute of Public Health, University of Cambridge, Cambridge, UK.; Department of Health Sciences, College of Life Sciences, University of Leicester, Leicester, UK.; Department of Public Health & Policy, Institute of Psychology, Health & Society, University of Liverpool, Liverpool, UK.; Imperial College London, London, UK; Centre for Population Health Sciences, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.; MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK; NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK; NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.; Imperial College London, London, UK.; Public Health England, London, UK.; Public Health England, London, UK; Imperial College London, London, UK.; King's College London, London, UK.; Institute for Health Metrics and Evaluation, Seattle, WA, USA.; UKCRC Centre of Excellence for Public Health Research (NI), Queens University of Belfast, Belfast, UK.; Institute for Health Metrics and Evaluation, Seattle, WA, USA; London School of Hygiene & Tropical Medicine, London, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Imperial College London, London, UK.; London School of Hygiene & Tropical Medicine, London, UK.; Imperial College London, London, UK.; University of Bath, Bath, UK.; Imperial College London, London, UK.; Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.; London School of Hygiene & Tropical Medicine, London, UK.; University College London, London, UK.; Institute for Health Metrics and Evaluation, Seattle, WA, USA.; Centre of Evidence-Based Dermatology, Queen's Medical Centre, Nottingham University Hospitals NHS Trust, Nottingham, UK.; King's College London, London, UK.; Bone and Joint Research Group, Royal Cornwall Hospital, Truro, UK.; Institute for Health Metrics and Evaluation, Seattle, WA, USA.","Lancet (London, England)",2018,"BACKGROUND:Previous studies have reported national and regional Global Burden of Disease (GBD) estimates for the UK. Because of substantial variation in health within the UK, action to improve it requires comparable estimates of disease burden and risks at country and local levels. The slowdown in the rate of improvement in life expectancy requires further investigation. We use GBD 2016 data on mortality, causes of death, and disability to analyse the burden of disease in the countries of the UK and within local authorities in England by deprivation quintile. METHODS:We extracted data from the GBD 2016 to estimate years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), and attributable risks from 1990 to 2016 for England, Scotland, Wales, Northern Ireland, the UK, and 150 English Upper-Tier Local Authorities. We estimated the burden of disease by cause of death, condition, year, and sex. We analysed the association between burden of disease and socioeconomic deprivation using the Index of Multiple Deprivation. We present results for all 264 GBD causes of death combined and the leading 20 specific causes, and all 84 GBD risks or risk clusters combined and 17 specific risks or risk clusters. FINDINGS:The leading causes of age-adjusted YLLs in all UK countries in 2016 were ischaemic heart disease, lung cancers, cerebrovascular disease, and chronic obstructive pulmonary disease. Age-standardised rates of YLLs for all causes varied by two times between local areas in England according to levels of socioeconomic deprivation (from 14 274 per 100 000 population [95% uncertainty interval 12 791-15 875] in Blackpool to 6888 [6145-7739] in Wokingham). Some Upper-Tier Local Authorities, particularly those in London, did better than expected for their level of deprivation. Allowing for differences in age structure, more deprived Upper-Tier Local Authorities had higher attributable YLLs for most major risk factors in the GBD. The population attributable fractions for all-cause YLLs for individual major risk factors varied across Upper-Tier Local Authorities. Life expectancy and YLLs have improved more slowly since 2010 in all UK countries compared with 1990-2010. In nine of 150 Upper-Tier Local Authorities, YLLs increased after 2010. For attributable YLLs, the rate of improvement slowed most substantially for cardiovascular disease and breast, colorectal, and lung cancers, and showed little change for Alzheimer's disease and other dementias. Morbidity makes an increasing contribution to overall burden in the UK compared with mortality. The age-standardised UK DALY rate for low back and neck pain (1795 [1258-2356]) was higher than for ischaemic heart disease (1200 [1155-1246]) or lung cancer (660 [642-679]). The leading causes of ill health (measured through YLDs) in the UK in 2016 were low back and neck pain, skin and subcutaneous diseases, migraine, depressive disorders, and sense organ disease. Age-standardised YLD rates varied much less than equivalent YLL rates across the UK, which reflects the relative scarcity of local data on causes of ill health. INTERPRETATION:These estimates at local, regional, and national level will allow policy makers to match resources and priorities to levels of burden and risk factors. Improvement in YLLs and life expectancy slowed notably after 2010, particularly in cardiovascular disease and cancer, and targeted actions are needed if the rate of improvement is to recover. A targeted policy response is also required to address the increasing proportion of burden due to morbidity, such as musculoskeletal problems and depression. Improving the quality and completeness of available data on these causes is an essential component of this response. FUNDING:Bill & Melinda Gates Foundation and Public Health England."
 30898389,https://doi.org/10.1016/j.injury.2019.03.003,Potentially preventable trauma deaths: A retrospective review.,"Beck B, Smith K, Mercier E, Bernard S, Jones C, Meadley B, Clair TS, Jennings PA, Nehme Z, Burke M, Bassed R, Fitzgerald M, Judson R, Teague W, Mitra B, Mathew J, Buck A, Varma D, Gabbe B, Bray J, McLellan S, Ford J, Siedenburg J, Cameron P.","Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Faculty of Medicine, Laval University, Quebec City, Quebec, Canada. Electronic address: ben.beck@monash.edu.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Centre for Research and Evaluation, Ambulance Victoria, Victoria, Australia; Department of Community Emergency Health and Paramedic Practice, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Faculty of Medicine, Laval University, Quebec City, Quebec, Canada.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Centre for Research and Evaluation, Ambulance Victoria, Victoria, Australia; The Intensive Care Unit, The Alfred Hospital.; Ambulance Victoria, Victoria, Australia.; Department of Community Emergency Health and Paramedic Practice, Monash University, Victoria, Australia; Ambulance Victoria, Victoria, Australia.; Department of Community Emergency Health and Paramedic Practice, Monash University, Victoria, Australia; Ambulance Victoria, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Department of Community Emergency Health and Paramedic Practice, Monash University, Victoria, Australia; Ambulance Victoria, Victoria, Australia; Emergency and Trauma Centre, The Alfred, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Centre for Research and Evaluation, Ambulance Victoria, Victoria, Australia; Department of Community Emergency Health and Paramedic Practice, Monash University, Victoria, Australia; Ambulance Victoria, Victoria, Australia.; Victorian Institute of Forensic Medicine, Victoria, Australia.; Victorian Institute of Forensic Medicine, Victoria, Australia; Department of Forensic Medicine, Monash University, Victoria, Australia.; Trauma Service, The Alfred, Victoria, Australia; National Trauma Research Institute, Victoria, Australia.; General Surgery, The Royal Melbourne Hospital, Victoria, Australia; Department of Surgery, The University of Melbourne, Victoria, Australia.; Trauma Service, The Royal Children's Hospital, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia; Surgical Research Group, Murdoch Children's Research Institute, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; National Trauma Research Institute, Victoria, Australia; Emergency and Trauma Centre, The Alfred, Victoria, Australia.; Trauma Service, The Alfred, Victoria, Australia; National Trauma Research Institute, Victoria, Australia; Emergency and Trauma Centre, The Alfred, Victoria, Australia.; Emergency Department, Royal Darwin Hospital, Northern Territory, Australia.; Department of Surgery, The University of Melbourne, Victoria, Australia; Radiology, The Alfred, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Health Data Research UK, Swansea University Medical School, Swansea University, UK.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Prehospital, Resuscitation and Emergency Care Research Unit (PRECRU), School of Nursing, Midwifery and Paramedicine, Curtin University, Perth, Western Australia, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; National Trauma Research Institute, Victoria, Australia; Emergency and Trauma Centre, The Alfred, Victoria, Australia.",Injury,2019,"BACKGROUND:Reviewing prehospital trauma deaths provides an opportunity to identify system improvements that may reduce trauma mortality. The objective of this study was to identify the number and rate of potentially preventable trauma deaths through expert panel reviews of prehospital and early in-hospital trauma deaths. METHODS:We conducted a retrospective review of prehospital and early in-hospital (<24 h) trauma deaths following a traumatic out-of-hospital cardiac arrest that were attended by Ambulance Victoria (AV) in the state of Victoria, Australia, between 2008 and 2014. Expert panels were used to review cases that had resuscitation attempted by paramedics and underwent a full autopsy. Patients with a mechanism of hanging, drowning or those with anatomical injuries deemed to be unsurvivable were excluded. RESULTS:Of the 1183 cases that underwent full autopsies, resuscitation was attempted by paramedics in 336 (28%) cases. Of these, 113 cases (34%) were deemed to have potentially survivable injuries and underwent expert panel review. There were 90 (80%) deaths that were not preventable, 19 (17%) potentially preventable deaths and 4 (3%) preventable deaths. Potentially preventable or preventable deaths represented 20% of those cases that underwent review and 7% of cases that had attempted resuscitation. CONCLUSIONS:The number of potentially preventable or preventable trauma deaths in the pre-hospital and early in-hospital resuscitation phase was low. Specific circumstances were identified in which the trauma system could be further improved."
 30487518,https://doi.org/10.1038/s41467-018-07345-0,Interethnic analyses of blood pressure loci in populations of East Asian and European descent.,"Takeuchi F, Akiyama M, Matoba N, Katsuya T, Nakatochi M, Tabara Y, Narita A, Saw WY, Moon S, Spracklen CN, Chai JF, Kim YJ, Zhang L, Wang C, Li H, Li H, Wu JY, Dorajoo R, Nierenberg JL, Wang YX, He J, Bennett DA, Takahashi A, Momozawa Y, Hirata M, Matsuda K, Rakugi H, Nakashima E, Isono M, Shirota M, Hozawa A, Ichihara S, Matsubara T, Yamamoto K, Kohara K, Igase M, Han S, Gordon-Larsen P, Huang W, Lee NR, Adair LS, Hwang MY, Lee J, Chee ML, Sabanayagam C, Zhao W, Liu J, Reilly DF, Sun L, Huo S, Edwards TL, Long J, Chang LC, Chen CH, Yuan JM, Koh WP, Friedlander Y, Kelly TN, Bin Wei W, Xu L, Cai H, Xiang YB, Lin K, Clarke R, Walters RG, Millwood IY, Li L, Chambers JC, Kooner JS, Elliott P, van der Harst P, International Genomics of Blood Pressure (iGEN-BP) Consortium, Chen Z, Sasaki M, Shu XO, Jonas JB, He J, Heng CK, Chen YT, Zheng W, Lin X, Teo YY, Tai ES, Cheng CY, Wong TY, Sim X, Mohlke KL, Yamamoto M, Kim BJ, Miki T, Nabika T, Yokota M, Kamatani Y, Kubo M, Kato N.","Medical Genomics Center, National Center for Global Health and Medicine, Tokyo, 162-8655, Japan.; Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.; Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.; Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan.; Data Coordinating Center, Department of Advanced Medicine, Nagoya University Hospital, Nagoya, 466-8560, Japan.; Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8507, Japan.; Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan.; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.; Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 363-951, Republic of Korea.; Department of Genetics, University of North Carolina, Chapel Hill, NC 27514, USA.; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.; Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 363-951, Republic of Korea.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore.; Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672, Singapore.; CAS Key Laboratory of Nutrition, Metabolism and Food safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.; State Key Laboratory of Oncogene and Related Genes and Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China.; Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan.; Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672, Singapore.; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.; Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China.; Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN 37203-1738, USA.; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.; Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.; Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.; Institute of Medical Science, The University of Tokyo, Tokyo, 108-8639, Japan.; Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, 277-8561, Japan.; Department of Geriatric and General Medicine, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan.; Division of Endocrinology and Diabetes, Department of Internal Medicine, Nagoya University Graduate School of Medicine, Nagoya, 466-8550, Japan.; Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, 162-8655, Japan.; Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan.; Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan.; Department of Environmental and Preventive Medicine, Jichi Medical University School of Medicine, Shimotsuke, 329-0498, Japan.; Department of Internal Medicine, School of Dentistry, Aichi Gakuin University, Nagoya, 470-0195, Japan.; Department of Medical Biochemistry, Kurume University School of Medicine, Kurume, 830-0011, Japan.; Faculty of Collaborative Regional Innovation, Ehime University, Matsuyama, 790-8577, Ehime, Japan.; Department of Geriatric Medicine, Ehime University Graduate School of Medicine, Toon, 791-0295, Ehime, Japan.; Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 363-951, Republic of Korea.; Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.; Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center and Shanghai Industrial Technology Institute (SITI), Shanghai, 201203, China.; USC-Office of Population Studies Foundation, University of San Carlos, Cebu City, 6000, Philippines.; Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.; Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 363-951, Republic of Korea.; Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 363-951, Republic of Korea.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore.; Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672, Singapore.; Merck Sharp Dohme Corp, Kenilworth, NJ 07033, USA.; CAS Key Laboratory of Nutrition, Metabolism and Food safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.; CAS Key Laboratory of Nutrition, Metabolism and Food safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.; Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN 37203-1738, USA.; Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN 37203-1738, USA.; Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan.; Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan.; Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.; Unit of Epidemiology, Hebrew University-Hadassah Braun School of Public Health, Jerusalem, P.O. Box 12272, Israel.; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.; Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China.; Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China.; Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN 37203-1738, USA.; State Key Laboratory of Oncogene and Related Genes and Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China.; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.; Chinese Academy of Medical Sciences, Beijing, 100006, China.; Department of Epidemiology and Biostatistics, Imperial College London, London, SW7 2AZ, UK.; National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK.; Medical Research Council-Public Health England (MRC-PHE) Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK.; Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, Netherlands.; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.; Iwate Tohoku Medical Megabank Organization, Iwate, 028-3694, Japan.; Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN 37203-1738, USA.; Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China.; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.; Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore.; Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan.; Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN 37203-1738, USA.; CAS Key Laboratory of Nutrition, Metabolism and Food safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore.; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.; Department of Genetics, University of North Carolina, Chapel Hill, NC 27514, USA.; Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan.; Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 363-951, Republic of Korea.; Department of Geriatric Medicine, Ehime University Graduate School of Medicine, Toon, 791-0295, Ehime, Japan.; Department of Functional Pathology, Shimane University Faculty of Medicine, Izumo, 693-0021, Japan.; Department of Genome Science, School of Dentistry, Aichi Gakuin University, Nagoya, 464-8650, Japan.; Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.; RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.; Medical Genomics Center, National Center for Global Health and Medicine, Tokyo, 162-8655, Japan. nokato@ri.ncgm.go.jp.",Nature communications,2018,"Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, we perform a multi-stage genome-wide association study for BP (max N = 289,038) principally in East Asians and meta-analysis in East Asians and Europeans. We report 19 new genetic loci and ancestry-specific BP variants, conforming to a common ancestry-specific variant association model. At 10 unique loci, distinct non-rare ancestry-specific variants colocalize within the same linkage disequilibrium block despite the significantly discordant effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect-sizes is 0.898 and 0.851 for systolic and diastolic BP, respectively. Some of the ancestry-specific association signals are also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in ethnic differences in complex traits such as BP."
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 30950797,https://doi.org/10.2196/12286,Applications of Machine Learning in Real-Life Digital Health Interventions: Review of the Literature.,"Triantafyllidis AK, Tsanas A.","Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece.; Usher Institute of Population Health Sciences and Informatics, Medical School, University of Edinburgh, Edinburgh, United Kingdom.",Journal of medical Internet research,2019,"BACKGROUND:Machine learning has attracted considerable research interest toward developing smart digital health interventions. These interventions have the potential to revolutionize health care and lead to substantial outcomes for patients and medical professionals. OBJECTIVE:Our objective was to review the literature on applications of machine learning in real-life digital health interventions, aiming to improve the understanding of researchers, clinicians, engineers, and policy makers in developing robust and impactful data-driven interventions in the health care domain. METHODS:We searched the PubMed and Scopus bibliographic databases with terms related to machine learning, to identify real-life studies of digital health interventions incorporating machine learning algorithms. We grouped those interventions according to their target (ie, target condition), study design, number of enrolled participants, follow-up duration, primary outcome and whether this had been statistically significant, machine learning algorithms used in the intervention, and outcome of the algorithms (eg, prediction). RESULTS:Our literature search identified 8 interventions incorporating machine learning in a real-life research setting, of which 3 (37%) were evaluated in a randomized controlled trial and 5 (63%) in a pilot or experimental single-group study. The interventions targeted depression prediction and management, speech recognition for people with speech disabilities, self-efficacy for weight loss, detection of changes in biopsychosocial condition of patients with multiple morbidity, stress management, treatment of phantom limb pain, smoking cessation, and personalized nutrition based on glycemic response. The average number of enrolled participants in the studies was 71 (range 8-214), and the average follow-up study duration was 69 days (range 3-180). Of the 8 interventions, 6 (75%) showed statistical significance (at the P=.05 level) in health outcomes. CONCLUSIONS:This review found that digital health interventions incorporating machine learning algorithms in real-life studies can be useful and effective. Given the low number of studies identified in this review and that they did not follow a rigorous machine learning evaluation methodology, we urge the research community to conduct further studies in intervention settings following evaluation principles and demonstrating the potential of machine learning in clinical practice."
-30984881,https://doi.org/10.12688/wellcomeopenres.15151.1,Causes of death among homeless people: a population-based cross-sectional study of linked hospitalisation and mortality data in England.,"Aldridge RW, Menezes D, Lewer D, Cornes M, Evans H, Blackburn RM, Byng R, Clark M, Denaxas S, Fuller J, Hewett N, Kilmister A, Luchenski S, Manthorpe J, McKee M, Neale J, Story A, Tinelli M, Whiteford M, Wurie F, Hayward A.","Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Community and Primary Care Research Group, University of Plymouth, Plymouth, Devon, PL6 8BX, UK.; Personal Social Services Research Unit, London School of Economics, London, WC2A 2AE, UK.; Institute of Health Informatics, University College London, London, NW1 2DA, UK.; NIHR Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Pathway Charity, Pathway Charity, London, NW1 2PG, UK.; Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Collaborative Centre for Inclusion Health, Institute of Epidemiology & Health Care, University College London, London, NW1 2DA, UK.; Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Department of Health Services Research & Policy, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.; National Addiction Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE1 1UL, UK.; Collaborative Centre for Inclusion Health, Institute of Epidemiology & Health Care, University College London, London, NW1 2DA, UK.; Personal Social Services Research Unit, London School of Economics, London, WC2A 2AE, UK.; Health Services Research, University of Liverpool, Liverpool, L69 3BX, UK.; Public Health England, London, NW9 5EQ, UK.; Collaborative Centre for Inclusion Health, Institute of Epidemiology & Health Care, University College London, London, NW1 2DA, UK.",Wellcome open research,2019,"Background: Homelessness has increased by 165% since 2010 in England, with evidence from many settings that those affected experience high levels of mortality. In this paper we examine the contribution of different causes of death to overall mortality in homeless people recently admitted to hospitals in England with specialist integrated homeless health and care (SIHHC) schemes.  Methods: We undertook an analysis of linked hospital admission records and mortality data for people attending any one of 17 SIHHC schemes between 1st November 2013 and 30th November 2016. Our primary outcome was death, which we analysed in subgroups of 10th version international classification of disease (ICD-10) specific deaths; and deaths from amenable causes. We compared our results to a sample of people living in areas of high social deprivation (IMD5 group). Results: We collected data on 3,882 individual homeless hospital admissions that were linked to 600 deaths. The median age of death was 51.6 years (interquartile range 42.7-60.2) for SIHHC and 71.5 for the IMD5 (60.67-79.0).  The top three underlying causes of death by ICD-10 chapter in the SIHHC group were external causes of death (21.7%; 130/600), cancer (19.0%; 114/600) and digestive disease (19.0%; 114/600).  The percentage of deaths due to an amenable cause after age and sex weighting was 30.2% in the homeless SIHHC group (181/600) compared to 23.0% in the IMD5 group (578/2,512). Conclusion: Nearly one in three homeless deaths were due to causes amenable to timely and effective health care. The high burden of amenable deaths highlights the extreme health harms of homelessness and the need for greater emphasis on prevention of homelessness and early healthcare interventions."
 31000744,https://doi.org/10.1038/s41598-019-42036-w,"Measuring social, environmental and health inequalities using deep learning and street imagery.","Suel E, Polak JW, Bennett JE, Ezzati M.","School of Public Health, Imperial College London, London, UK. esra.suel@imperial.ac.uk.; Urban Systems Laboratory, Imperial College London, London, SW7 2AZ, United Kingdom.; School of Public Health, Imperial College London, London, UK.; School of Public Health, Imperial College London, London, UK.",Scientific reports,2019,"Cities are home to an increasing majority of the world's population. Currently, it is difficult to track social, economic, environmental and health outcomes in cities with high spatial and temporal resolution, needed to evaluate policies regarding urban inequalities. We applied a deep learning approach to street images for measuring spatial distributions of income, education, unemployment, housing, living environment, health and crime. Our model predicts different outcomes directly from raw images without extracting intermediate user-defined features. To evaluate the performance of the approach, we first trained neural networks on a subset of images from London using ground truth data at high spatial resolution from official statistics. We then compared how trained networks separated the best-off from worst-off deciles for different outcomes in images not used in training. The best performance was achieved for quality of the living environment and mean income. Allocation was least successful for crime and self-reported health (but not objectively measured health). We also evaluated how networks trained in London predict outcomes three other major cities in the UK: Birmingham, Manchester, and Leeds. The transferability analysis showed that networks trained in London, fine-tuned with only 1% of images in other cities, achieved performances similar to ones from trained on data from target cities themselves. Our findings demonstrate that street imagery has the potential complement traditional survey-based and administrative data sources for high-resolution urban surveillance to measure inequalities and monitor the impacts of policies that aim to address them."
+30984881,https://doi.org/10.12688/wellcomeopenres.15151.1,Causes of death among homeless people: a population-based cross-sectional study of linked hospitalisation and mortality data in England.,"Aldridge RW, Menezes D, Lewer D, Cornes M, Evans H, Blackburn RM, Byng R, Clark M, Denaxas S, Fuller J, Hewett N, Kilmister A, Luchenski S, Manthorpe J, McKee M, Neale J, Story A, Tinelli M, Whiteford M, Wurie F, Hayward A.","Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Public Health Data Science, Institute of Health Informatics, University College London, London, NW1 2DA, UK.; Community and Primary Care Research Group, University of Plymouth, Plymouth, Devon, PL6 8BX, UK.; Personal Social Services Research Unit, London School of Economics, London, WC2A 2AE, UK.; Institute of Health Informatics, University College London, London, NW1 2DA, UK.; NIHR Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Pathway Charity, Pathway Charity, London, NW1 2PG, UK.; Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Collaborative Centre for Inclusion Health, Institute of Epidemiology & Health Care, University College London, London, NW1 2DA, UK.; Health and Social Care Workforce Research Unit, King's College London, London, SE1 1UL, UK.; Department of Health Services Research & Policy, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.; National Addiction Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE1 1UL, UK.; Collaborative Centre for Inclusion Health, Institute of Epidemiology & Health Care, University College London, London, NW1 2DA, UK.; Personal Social Services Research Unit, London School of Economics, London, WC2A 2AE, UK.; Health Services Research, University of Liverpool, Liverpool, L69 3BX, UK.; Public Health England, London, NW9 5EQ, UK.; Collaborative Centre for Inclusion Health, Institute of Epidemiology & Health Care, University College London, London, NW1 2DA, UK.",Wellcome open research,2019,"Background: Homelessness has increased by 165% since 2010 in England, with evidence from many settings that those affected experience high levels of mortality. In this paper we examine the contribution of different causes of death to overall mortality in homeless people recently admitted to hospitals in England with specialist integrated homeless health and care (SIHHC) schemes.  Methods: We undertook an analysis of linked hospital admission records and mortality data for people attending any one of 17 SIHHC schemes between 1st November 2013 and 30th November 2016. Our primary outcome was death, which we analysed in subgroups of 10th version international classification of disease (ICD-10) specific deaths; and deaths from amenable causes. We compared our results to a sample of people living in areas of high social deprivation (IMD5 group). Results: We collected data on 3,882 individual homeless hospital admissions that were linked to 600 deaths. The median age of death was 51.6 years (interquartile range 42.7-60.2) for SIHHC and 71.5 for the IMD5 (60.67-79.0).  The top three underlying causes of death by ICD-10 chapter in the SIHHC group were external causes of death (21.7%; 130/600), cancer (19.0%; 114/600) and digestive disease (19.0%; 114/600).  The percentage of deaths due to an amenable cause after age and sex weighting was 30.2% in the homeless SIHHC group (181/600) compared to 23.0% in the IMD5 group (578/2,512). Conclusion: Nearly one in three homeless deaths were due to causes amenable to timely and effective health care. The high burden of amenable deaths highlights the extreme health harms of homelessness and the need for greater emphasis on prevention of homelessness and early healthcare interventions."
+31104603,https://doi.org/10.1098/rstb.2018.0276,Outbreak analytics: a developing data science for informing the response to emerging pathogens.,"Polonsky JA, Baidjoe A, Kamvar ZN, Cori A, Durski K, Edmunds WJ, Eggo RM, Funk S, Kaiser L, Keating P, de Waroux OLP, Marks M, Moraga P, Morgan O, Nouvellet P, Ratnayake R, Roberts CH, Whitworth J, Jombart T.","1 Department of Health Emergency Information and Risk Assessment, World Health Organization , Avenue Appia 20, 1211 Geneva , Switzerland.; 4 Department of Infectious Disease Epidemiology, School of Public Health, MRC Centre for Global Infectious Disease Analysis, Imperial College London , Medical School Building, St Mary's Campus, Norfolk Place London W2 1PG , UK.; 4 Department of Infectious Disease Epidemiology, School of Public Health, MRC Centre for Global Infectious Disease Analysis, Imperial College London , Medical School Building, St Mary's Campus, Norfolk Place London W2 1PG , UK.; 4 Department of Infectious Disease Epidemiology, School of Public Health, MRC Centre for Global Infectious Disease Analysis, Imperial College London , Medical School Building, St Mary's Campus, Norfolk Place London W2 1PG , UK.; 2 Department of Infectious Hazard Management, World Health Organization , Avenue Appia 20, 1211 Geneva , Switzerland.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 3 Faculty of Medicine, University of Geneva , 1 rue Michel-Servet, 1211 Geneva , Switzerland.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 7 Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 10 Centre for Health Informatics, Computing and Statistics (CHICAS), Lancaster Medical School, Lancaster University , Lancaster LA1 4YW , UK.; 1 Department of Health Emergency Information and Risk Assessment, World Health Organization , Avenue Appia 20, 1211 Geneva , Switzerland.; 4 Department of Infectious Disease Epidemiology, School of Public Health, MRC Centre for Global Infectious Disease Analysis, Imperial College London , Medical School Building, St Mary's Campus, Norfolk Place London W2 1PG , UK.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 7 Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine , Keppel St, London WC1E 7HT , UK.; 4 Department of Infectious Disease Epidemiology, School of Public Health, MRC Centre for Global Infectious Disease Analysis, Imperial College London , Medical School Building, St Mary's Campus, Norfolk Place London W2 1PG , UK.","Philosophical transactions of the Royal Society of London. Series B, Biological sciences",2019,"Despite continued efforts to improve health systems worldwide, emerging pathogen epidemics remain a major public health concern. Effective response to such outbreaks relies on timely intervention, ideally informed by all available sources of data. The collection, visualization and analysis of outbreak data are becoming increasingly complex, owing to the diversity in types of data, questions and available methods to address them. Recent advances have led to the rise of outbreak analytics, an emerging data science focused on the technological and methodological aspects of the outbreak data pipeline, from collection to analysis, modelling and reporting to inform outbreak response. In this article, we assess the current state of the field. After laying out the context of outbreak response, we critically review the most common analytics components, their inter-dependencies, data requirements and the type of information they can provide to inform operations in real time. We discuss some challenges and opportunities and conclude on the potential role of outbreak analytics for improving our understanding of, and response to outbreaks of emerging pathogens. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'."
 30423068,https://doi.org/10.1093/bioinformatics/bty605,Ontology-based validation and identification of regulatory phenotypes.,"Kulmanov M, Schofield PN, Gkoutos GV, Hoehndorf R.","Computer, Electrical and Mathematical Sciences and Engineering Division, Computational Bioscience Research Centre, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.; Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.; College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, UK.; Computer, Electrical and Mathematical Sciences and Engineering Division, Computational Bioscience Research Centre, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.","Bioinformatics (Oxford, England)",2018,"Motivation:Function annotations of gene products, and phenotype annotations of genotypes, provide valuable information about molecular mechanisms that can be utilized by computational methods to identify functional and phenotypic relatedness, improve our understanding of disease and pathobiology, and lead to discovery of drug targets. Identifying functions and phenotypes commonly requires experiments which are time-consuming and expensive to carry out; creating the annotations additionally requires a curator to make an assertion based on reported evidence. Support to validate the mutual consistency of functional and phenotype annotations as well as a computational method to predict phenotypes from function annotations, would greatly improve the utility of function annotations. Results:We developed a novel ontology-based method to validate the mutual consistency of function and phenotype annotations. We apply our method to mouse and human annotations, and identify several inconsistencies that can be resolved to improve overall annotation quality. We also apply our method to the rule-based prediction of regulatory phenotypes from functions and demonstrate that we can predict these phenotypes with Fmax of up to 0.647. Availability and implementation:https://github.com/bio-ontology-research-group/phenogocon."
 29716529,https://doi.org/10.1186/s12883-018-1058-8,Severe localised granulomatosis with polyangiitis (Wegener's granulomatosis) manifesting with extensive cranial nerve palsies and cranial diabetes insipidus: a case report and literature review.,"Peters JE, Gupta V, Saeed IT, Offiah C, Jawad ASM.","Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, Worts Causeway, University of Cambridge, Cambridge, CB1 8RN, UK. jp549@cam.ac.uk.; Department of Rheumatology, The Royal London and Mile End Hospitals, Barts Health NHS Trust, Bancroft Road, London, E1 4DG, UK.; Department of Histopathology, Queen's Hospital, Rom Valley Road, Romford, RM7 0AG, UK.; Department of Radiology, The Royal London Hospital, Barts Health NHS Trust, Whitechapel Road, London, E1 1BB, UK.; Department of Rheumatology, The Royal London and Mile End Hospitals, Barts Health NHS Trust, Bancroft Road, London, E1 4DG, UK.",BMC neurology,2018,"BACKGROUND:Granulomatosis with polyangiitis (GPA, formerly Wegener's granulomatosis) is a multisystem vasculitis of small- to medium-sized blood vessels. Cranial involvement can result in cranial nerve palsies and, rarely, pituitary infiltration. CASE PRESENTATION:We describe the case of a 32 year-old woman with limited but severe GPA manifesting as progressive cranial nerve palsies and pituitary dysfunction. Our patient initially presented with localised ENT involvement, but despite treatment with methotrexate, she deteriorated. Granulomatous inflammatory tissue around the skull base resulted in cavernous sinus syndrome, facial nerve palsy, palsies of cranial nerves IX-XII (Collet-Sicard syndrome), and the rare complication of cranial diabetes insipidus due to pituitary infiltration. The glossopharyngeal, vagus and accessory nerve palsies resulted in severe dysphagia and she required nasogastric tube feeding. Her neurological deficits substantially improved with treatment including high dose corticosteroid, cyclophosphamide and rituximab. CONCLUSIONS:This case emphasises that serious morbidity can arise from localised cranial Wegener's granulomatosis in the absence of systemic disease. In such cases intensive induction immunosuppression is required. Analysis of previously reported cases of pituitary involvement in GPA reveals that this rare complication predominantly affects female patients."
 30381314,https://doi.org/10.1136/bmjopen-2018-026290,Study protocol for investigating the impact of community home modification services on hospital utilisation for fall injuries: a controlled longitudinal study using data linkage.,"Hollinghurst J, Akbari A, Fry R, Watkins A, Berridge D, Clegg A, Hillcoat-Nalletamby S, Williams N, Lyons R, Mizen A, Walters A, Johnson R, Rodgers S.","Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; University of Leeds (Bradford Teaching Hospital), Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK.; College of Human and Health Sciences, Swansea University, Swansea, UK.; Care & Repair Cymru, Cardiff, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.; Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.",BMJ open,2018,"INTRODUCTION:This study will evaluate the effectiveness of home adaptations, both in preventing hospital admissions due to falls for older people, and improving timely discharge. Results will provide evidence for services at the interface between health and social care, informing policies seeking to promote healthy ageing through prudent healthcare and fall prevention. METHODS AND ANALYSIS:All individuals living in Wales, UK, aged 60 years and over, will be included in the study using anonymised linked data from the Secure Anonymised Information Linkage Databank. We will use a national database of home modifications implemented by the charity organisation Care & Repair Cymru (C&R) from 2009 to 2017 to define an intervention cohort. We will use the electronic Frailty Index to assign individual levels of frailty (fit, mild, moderate or severe) and use these to create a comparator group (non-C&R) of people who have not received a C&R intervention. Coprimary outcomes will be quarterly numbers of emergency hospital admissions attributed to falls at home, and the associated length of stay. Secondary outcomes include the time in moving to a care home following a fall, and the indicative financial costs of care for individuals who had a fall. We will use appropriate multilevel generalised linear models to analyse the number of hospital admissions related to falls. We will use Cox proportional hazard models to compare the length of stay for fall-related hospital admissions and the time in moving to a care home between the C&R and non-C&R cohorts. We will assess the impact per frailty group, correct for population migration and adjust for confounding variables. Indicative costs will be calculated using financial codes for individual-level hospital stays. Results will provide evidence for services at the interface between health and social care, informing policies seeking to promote healthy ageing through prudent healthcare and prevention. ETHICS AND DISSEMINATION:Information governance requirements for the use of record-linked data have been approved and only anonymised data will be used in our analysis. Our results will be submitted for publication in peer-reviewed journals. We will also work with lay members and the knowledge transfer team at Swansea University to create communication and dissemination materials on key findings."
+30727941,https://doi.org/10.1186/s12859-019-2633-8,DeepPVP: phenotype-based prioritization of causative variants using deep learning.,"Boudellioua I, Kulmanov M, Schofield PN, Gkoutos GV, Hoehndorf R.","Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia.; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia.; Department of Physiology, Development & Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK.; College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, B15 2TT, UK.; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia. robert.hoehndorf@kaust.edu.sa.",BMC bioinformatics,2019,"BACKGROUND:Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In these methods, pathogenicity prediction is combined with a semantic similarity measure to prioritize not only variants that are likely to be dysfunctional but those that are likely involved in the pathogenesis of a patient's phenotype. RESULTS:We have developed DeepPVP, a variant prioritization method that combined automated inference with deep neural networks to identify the likely causative variants in whole exome or whole genome sequence data. We demonstrate that DeepPVP performs significantly better than existing methods, including phenotype-based methods that use similar features. DeepPVP is freely available at https://github.com/bio-ontology-research-group/phenomenet-vp . CONCLUSIONS:DeepPVP further improves on existing variant prioritization methods both in terms of speed as well as accuracy."
 30532623,https://doi.org/10.3897/BDJ.6.e29232,"Modifier Ontologies for frequency, certainty, degree, and coverage phenotype modifier.","Endara L, Thessen AE, Cole HA, Walls R, Gkoutos G, Cao Y, Chong SS, Cui H.","University of Florida, Gainesville, United States of America University of Florida Gainesville United States of America.; The Ronin Institute for Independent Scholarship, Monclair, NJ, United States of America The Ronin Institute for Independent Scholarship Monclair, NJ United States of America.; Science and Technology Branch, Agriculture and Agri-Food Canada, Government of Canada, Ottawa, Canada Science and Technology Branch, Agriculture and Agri-Food Canada, Government of Canada Ottawa Canada.; CyVerse, Tucson, United States of America CyVerse Tucson United States of America.; College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham Birmingham United Kingdom.; Center for Studies of Information Resources, Wuhan Universtity, Wuhan, China Center for Studies of Information Resources, Wuhan Universtity Wuhan China.; National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, Santa Barbara, United States of America National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara Santa Barbara United States of America.; University of Arizona, Tucson, United States of America University of Arizona Tucson United States of America.",Biodiversity data journal,2018,"Background: When phenotypic characters are described in the literature, they may be constrained or clarified with additional information such as the location or degree of expression, these terms are called ""modifiers"". With effort underway to convert narrative character descriptions to computable data, ontologies for such modifiers are needed. Such ontologies can also be used to guide term usage in future publications. Spatial and method modifiers are the subjects of ontologies that already have been developed or are under development. In this work, frequency (e.g., rarely, usually), certainty (e.g., probably, definitely), degree (e.g., slightly, extremely), and coverage modifiers (e.g., sparsely, entirely) are collected, reviewed, and used to create two modifier ontologies with different design considerations. The basic goal is to express the sequential relationships within a type of modifiers, for example, usually is more frequent than rarely, in order to allow data annotated with ontology terms to be classified accordingly. Method: Two designs are proposed for the ontology, both using the list pattern: a closed ordered list (i.e., five-bin design) and an open ordered list design. The five-bin design puts the modifier terms into a set of 5 fixed bins with interval object properties, for example, one_level_more/less_frequently_than, where new terms can only be added as synonyms to existing classes. The open list approach starts with 5 bins, but supports the extensibility of the list via ordinal properties, for example, more/less_frequently_than, allowing new terms to be inserted as a new class anywhere in the list. The consequences of the different design decisions are discussed in the paper. CharaParser was used to extract modifiers from plant, ant, and other taxonomic descriptions. After a manual screening, 130 modifier words were selected as the candidate terms for the modifier ontologies. Four curators/experts (three biologists and one information scientist specialized in biosemantics) reviewed and categorized the terms into 20 bins using the Ontology Term Organizer (OTO) (http://biosemantics.arizona.edu/OTO). Inter-curator variations were reviewed and expressed in the final ontologies. Results: Frequency, certainty, degree, and coverage terms with complete agreement among all curators were used as class labels or exact synonyms. Terms with different interpretations were either excluded or included using ""broader synonym"" or ""not recommended"" annotation properties. These annotations explicitly allow for the user to be aware of the semantic ambiguity associated with the terms and whether they should be used with caution or avoided. Expert categorization results showed that 16 out of 20 bins contained terms with full agreements, suggesting differentiating the modifiers into 5 levels/bins balances the need to differentiate modifiers and the need for the ontology to reflect user consensus. Two ontologies, developed using the Protege ontology editor, are made available as OWL files and can be downloaded from https://github.com/biosemantics/ontologies. Contribution: We built the first two modifier ontologies following a consensus-based approach with terms commonly used in taxonomic literature. The five-bin ontology has been used in the Explorer of Taxon Concepts web toolkit to compute the similarity between characters extracted from literature to facilitate taxon concepts alignments. The two ontologies will also be used in an ontology-informed authoring tool for taxonomists to facilitate consistency in modifier term usage."
 30279426,https://doi.org/10.1038/s41598-018-32876-3,OligoPVP: Phenotype-driven analysis of individual genomic information to prioritize oligogenic disease variants.,"Boudellioua I, Kulmanov M, Schofield PN, Gkoutos GV, Hoehndorf R.","Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.; Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.; Department of Physiology, Development & Neuroscience, University of Cambridge, Cambridge, UK.; College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, B15 2TT, Birmingham, United Kingdom.; Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. robert.hoehndorf@kaust.edu.sa.",Scientific reports,2018,"An increasing number of disorders have been identified for which two or more distinct alleles in two or more genes are required to either cause the disease or to significantly modify its onset, severity or phenotype. It is difficult to discover such interactions using existing approaches. The purpose of our work is to develop and evaluate a system that can identify combinations of alleles underlying digenic and oligogenic diseases in individual whole exome or whole genome sequences. Information that links patient phenotypes to databases of gene-phenotype associations observed in clinical or non-human model organism research can provide useful information and improve variant prioritization for genetic diseases. Additional background knowledge about interactions between genes can be utilized to identify sets of variants in different genes in the same individual which may then contribute to the overall disease phenotype. We have developed OligoPVP, an algorithm that can be used to prioritize causative combinations of variants in digenic and oligogenic diseases, using whole exome or whole genome sequences together with patient phenotypes as input. We demonstrate that OligoPVP has significantly improved performance when compared to state of the art pathogenicity detection methods in the case of digenic diseases. Our results show that OligoPVP can efficiently prioritize sets of variants in digenic diseases using a phenotype-driven approach and identify etiologically important variants in whole genomes. OligoPVP naturally extends to oligogenic disease involving interactions between variants in two or more genes. It can be applied to the identification of multiple interacting candidate variants contributing to phenotype, where the action of modifier genes is suspected from pedigree analysis or failure of traditional causative variant identification."
 30240446,https://doi.org/10.1371/journal.pone.0203896,Polygenic risk scores for major depressive disorder and neuroticism as predictors of antidepressant response: Meta-analysis of three treatment cohorts.,"Ward J, Graham N, Strawbridge RJ, Ferguson A, Jenkins G, Chen W, Hodgson K, Frye M, Weinshilboum R, Uher R, Lewis CM, Biernacka J, Smith DJ.","Institute of Health And Wellbeing, University of Glasgow, Glasgow, Scotland.; Institute of Health And Wellbeing, University of Glasgow, Glasgow, Scotland.; Institute of Health And Wellbeing, University of Glasgow, Glasgow, Scotland.; Institute of Health And Wellbeing, University of Glasgow, Glasgow, Scotland.; Mayo Clinic, Rochester, MN, United States of America.; St. Jude Children's Research Hospital, Memphis, TN, United States of America.; King's College London, London, England.; Mayo Clinic, Rochester, MN, United States of America.; Mayo Clinic, Rochester, MN, United States of America.; Dalhousie University, Halifax, Canada.; King's College London, London, England.; Mayo Clinic, Rochester, MN, United States of America.; Institute of Health And Wellbeing, University of Glasgow, Glasgow, Scotland.",PloS one,2018,"There are currently no reliable approaches for correctly identifying which patients with major depressive disorder (MDD) will respond well to antidepressant therapy. However, recent genetic advances suggest that Polygenic Risk Scores (PRS) could allow MDD patients to be stratified for antidepressant response. We used PRS for MDD and PRS for neuroticism as putative predictors of antidepressant response within three treatment cohorts: The Genome-based Therapeutic Drugs for Depression (GENDEP) cohort, and 2 sub-cohorts from the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomics Study PRGN-AMPS (total patient number = 760). Results across cohorts were combined via meta-analysis within a random effects model. Overall, PRS for MDD and neuroticism did not significantly predict antidepressant response but there was a consistent direction of effect, whereby greater genetic loading for both MDD (best MDD result, p < 5*10-5 MDD-PRS at 4 weeks, β = -0.019, S.E = 0.008, p = 0.01) and neuroticism (best neuroticism result, p < 0.1 neuroticism-PRS at 8 weeks, β = -0.017, S.E = 0.008, p = 0.03) were associated with less favourable response. We conclude that the PRS approach may offer some promise for treatment stratification in MDD and should now be assessed within larger clinical cohorts."
-30727941,https://doi.org/10.1186/s12859-019-2633-8,DeepPVP: phenotype-based prioritization of causative variants using deep learning.,"Boudellioua I, Kulmanov M, Schofield PN, Gkoutos GV, Hoehndorf R.","Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia.; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia.; Department of Physiology, Development & Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK.; College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, B15 2TT, UK.; Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Kingdom of Saudi Arabia. robert.hoehndorf@kaust.edu.sa.",BMC bioinformatics,2019,"BACKGROUND:Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In these methods, pathogenicity prediction is combined with a semantic similarity measure to prioritize not only variants that are likely to be dysfunctional but those that are likely involved in the pathogenesis of a patient's phenotype. RESULTS:We have developed DeepPVP, a variant prioritization method that combined automated inference with deep neural networks to identify the likely causative variants in whole exome or whole genome sequence data. We demonstrate that DeepPVP performs significantly better than existing methods, including phenotype-based methods that use similar features. DeepPVP is freely available at https://github.com/bio-ontology-research-group/phenomenet-vp . CONCLUSIONS:DeepPVP further improves on existing variant prioritization methods both in terms of speed as well as accuracy."
 29457906,https://doi.org/10.1021/acs.jproteome.7b00879,Optimized Phenotypic Biomarker Discovery and Confounder Elimination via Covariate-Adjusted Projection to Latent Structures from Metabolic Spectroscopy Data.,"Posma JM, Garcia-Perez I, Ebbels TMD, Lindon JC, Stamler J, Elliott P, Holmes E, Nicholson JK.","Investigative Medicine, Department of Medicine, Faculty of Medicine , Imperial College London , W12 0NN London , United Kingdom.; Department of Preventive Medicine, Feinberg School of Medicine , Northwestern University , Chicago , Illinois 60611 , United States.",Journal of proteome research,2018,"Metabolism is altered by genetics, diet, disease status, environment, and many other factors. Modeling either one of these is often done without considering the effects of the other covariates. Attributing differences in metabolic profile to one of these factors needs to be done while controlling for the metabolic influence of the rest. We describe here a data analysis framework and novel confounder-adjustment algorithm for multivariate analysis of metabolic profiling data. Using simulated data, we show that similar numbers of true associations and significantly less false positives are found compared to other commonly used methods. Covariate-adjusted projections to latent structures (CA-PLS) are exemplified here using a large-scale metabolic phenotyping study of two Chinese populations at different risks for cardiovascular disease. Using CA-PLS, we find that some previously reported differences are actually associated with external factors and discover a number of previously unreported biomarkers linked to different metabolic pathways. CA-PLS can be applied to any multivariate data where confounding may be an issue and the confounder-adjustment procedure is translatable to other multivariate regression techniques."
-31101093,https://doi.org/10.1186/s12889-019-6888-9,Educational and health outcomes of children and adolescents receiving antiepileptic medication: Scotland-wide record linkage study of 766 244 schoolchildren.,"Fleming M, Fitton CA, Steiner MFC, McLay JS, Clark D, King A, Mackay DF, Pell JP.","Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK. michael.fleming@glasgow.ac.uk.; Department of Child Health, University of Aberdeen, Aberdeen, AB25 2ZG, UK.; Department of Child Health, University of Aberdeen, Aberdeen, AB25 2ZG, UK.; Department of Child Health, University of Aberdeen, Aberdeen, AB25 2ZG, UK.; Information Services Division, Edinburgh, EH12 9EB, UK.; ScotXed, Scottish Government, Edinburgh, EH6 6QQ, UK.; Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK.; Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK.",BMC public health,2019,"BACKGROUND:Childhood epilepsy can adversely affect education and employment in addition to health. Previous studies are small or highly selective producing conflicting results. This retrospective cohort study aims to compare educational and health outcomes of children receiving antiepileptic medication versus peers. METHODS:Record linkage of Scotland-wide databases covering dispensed prescriptions, acute and psychiatric hospitalisations, maternity records, deaths, annual pupil census, school absences/exclusions, special educational needs, school examinations, and (un)employment provided data on 766,244 children attending Scottish schools between 2009 and 2013. Outcomes were adjusted for sociodemographic and maternity confounders and comorbid conditions. RESULTS:Compared with peers, children on antiepileptic medication were more likely to experience school absence (Incidence Rate Ratio [IRR] 1.43, 95% CI: 1.38, 1.48), special educational needs (Odds ratio [OR] 9.60, 95% CI: 9.02, 10.23), achieve the lowest level of attainment (OR 3.43, 95% CI: 2.74, 4.29) be unemployed (OR 1.82, 95% CI: 1.60, 2.07), be admitted to hospital (Hazard Ratio [HR] 3.56, 95% CI: 3.42, 3.70), and die (HR 22.02, 95% CI: 17.00, 28.53). Absenteeism partly explained poorer attainment and higher unemployment. Girls and younger children on antiepileptic medication had higher risk of poor outcomes. CONCLUSIONS:Children on antiepileptic medication fare worse than peers across educational and health outcomes. In order to reduce school absenteeism and mitigate its effects, children with epilepsy should receive integrated care from a multidisciplinary team that spans education and healthcare."
 30181555,https://doi.org/10.1038/s41398-018-0236-1,"Genetics of self-reported risk-taking behaviour, trans-ethnic consistency and relevance to brain gene expression.","Strawbridge RJ, Ward J, Lyall LM, Tunbridge EM, Cullen B, Graham N, Ferguson A, Johnston KJA, Lyall DM, Mackay D, Cavanagh J, Howard DM, Adams MJ, Deary I, Escott-Price V, O'Donovan M, McIntosh AM, Bailey MES, Pell JP, Harrison PJ, Smith DJ.","Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK. rona.strawbridge@glasgow.ac.uk.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Department of Psychiatry, University of Oxford, Oxford, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK.; Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK.; Department of Psychology, University of Edinburgh, Edinburgh, EH8 9YL, UK.; MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.; MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.; Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK.; School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Department of Psychiatry, University of Oxford, Oxford, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.",Translational psychiatry,2018,"Risk-taking behaviour is an important component of several psychiatric disorders, including attention-deficit hyperactivity disorder, schizophrenia and bipolar disorder. Previously, two genetic loci have been associated with self-reported risk taking and significant genetic overlap with psychiatric disorders was identified within a subsample of UK Biobank. Using the white British participants of the full UK Biobank cohort (n = 83,677 risk takers versus 244,662 controls) for our primary analysis, we conducted a genome-wide association study of self-reported risk-taking behaviour. In secondary analyses, we assessed sex-specific effects, trans-ethnic heterogeneity and genetic overlap with psychiatric traits. We also investigated the impact of risk-taking-associated SNPs on both gene expression and structural brain imaging. We identified 10 independent loci for risk-taking behaviour, of which eight were novel and two replicated previous findings. In addition, we found two further sex-specific risk-taking loci. There were strong positive genetic correlations between risk-taking and attention-deficit hyperactivity disorder, bipolar disorder and schizophrenia. Index genetic variants demonstrated effects generally consistent with the discovery analysis in individuals of non-British White, South Asian, African-Caribbean or mixed ethnicity. Polygenic risk scores comprising alleles associated with increased risk taking were associated with lower white matter integrity. Genotype-specific expression pattern analyses highlighted DPYSL5, CGREF1 and C15orf59 as plausible candidate genes. Overall, our findings substantially advance our understanding of the biology of risk-taking behaviour, including the possibility of sex-specific contributions, and reveal consistency across ethnicities. We further highlight several putative novel candidate genes, which may mediate these genetic effects."
 30745170,https://doi.org/10.1016/j.ebiom.2019.02.005,"Identification of novel genome-wide associations for suicidality in UK Biobank, genetic correlation with psychiatric disorders and polygenic association with completed suicide.","Strawbridge RJ, Ward J, Ferguson A, Graham N, Shaw RJ, Cullen B, Pearsall R, Lyall LM, Johnston KJA, Niedzwiedz CL, Pell JP, Mackay D, Martin JL, Lyall DM, Bailey MES, Smith DJ.","Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK; Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK; Division of Psychiatry, College of Medicine, University of Edinburgh, UK; School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK. Electronic address: Daniel.Smith@glasgow.ac.uk.",EBioMedicine,2019,"BACKGROUND:Suicide is a major issue for global public health. Suicidality describes a broad spectrum of thoughts and behaviours, some of which are common in the general population. Although suicide results from a complex interaction of multiple social and psychological factors, predisposition to suicidality is at least partly genetic. METHODS:Ordinal genome-wide association study of suicidality in the UK Biobank cohort comparing: 'no suicidality' controls (N = 83,557); 'thoughts that life was not worth living' (N = 21,063); 'ever contemplated self-harm' (N = 13,038); 'act of deliberate self-harm in the past' (N = 2498); and 'previous suicide attempt' (N = 2666). OUTCOMES:We identified three novel genome-wide significant loci for suicidality (on chromosomes nine, 11 and 13) and moderate-to-strong genetic correlations between suicidality and a range of psychiatric disorders, most notably depression (rg 0·81). INTERPRETATION:These findings provide new information about genetic variants relating to increased risk of suicidal thoughts and behaviours. Future work should assess the extent to which polygenic risk scores for suicidality, in combination with non-genetic risk factors, may be useful for stratified approaches to suicide prevention at a population level. FUND: UKRI Innovation-HDR-UK Fellowship (MR/S003061/1). MRC Mental Health Data Pathfinder Award (MC_PC_17217). MRC Doctoral Training Programme Studentship at the University of Glasgow (MR/K501335/1). MRC Doctoral Training Programme Studentship at the Universities of Glasgow and Edinburgh. UKRI Innovation Fellowship (MR/R024774/1)."
 30742608,https://doi.org/10.1371/journal.pcbi.1006785,"Assessing the performance of real-time epidemic forecasts: A case study of Ebola in the Western Area region of Sierra Leone, 2014-15.","Funk S, Camacho A, Kucharski AJ, Lowe R, Eggo RM, Edmunds WJ.","Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.",PLoS computational biology,2019,"Real-time forecasts based on mathematical models can inform critical decision-making during infectious disease outbreaks. Yet, epidemic forecasts are rarely evaluated during or after the event, and there is little guidance on the best metrics for assessment. Here, we propose an evaluation approach that disentangles different components of forecasting ability using metrics that separately assess the calibration, sharpness and bias of forecasts. This makes it possible to assess not just how close a forecast was to reality but also how well uncertainty has been quantified. We used this approach to analyse the performance of weekly forecasts we generated in real time for Western Area, Sierra Leone, during the 2013-16 Ebola epidemic in West Africa. We investigated a range of forecast model variants based on the model fits generated at the time with a semi-mechanistic model, and found that good probabilistic calibration was achievable at short time horizons of one or two weeks ahead but model predictions were increasingly unreliable at longer forecasting horizons. This suggests that forecasts may have been of good enough quality to inform decision making based on predictions a few weeks ahead of time but not longer, reflecting the high level of uncertainty in the processes driving the trajectory of the epidemic. Comparing forecasts based on the semi-mechanistic model to simpler null models showed that the best semi-mechanistic model variant performed better than the null models with respect to probabilistic calibration, and that this would have been identified from the earliest stages of the outbreak. As forecasts become a routine part of the toolkit in public health, standards for evaluation of performance will be important for assessing quality and improving credibility of mathematical models, and for elucidating difficulties and trade-offs when aiming to make the most useful and reliable forecasts."
@@ -18,19 +18,29 @@ id,doi,title,authorString,authorAffiliations,journalTitle,pubYear,abstract
 30120083,https://doi.org/10.1016/j.ebiom.2018.08.004,"Genome-Wide Association Study of Circadian Rhythmicity in 71,500 UK Biobank Participants and Polygenic Association with Mood Instability.","Ferguson A, Lyall LM, Ward J, Strawbridge RJ, Cullen B, Graham N, Niedzwiedz CL, Johnston KJA, MacKay D, Biello SM, Pell JP, Cavanagh J, McIntosh AM, Doherty A, Bailey MES, Lyall DM, Wyse CA, Smith DJ.","Institute of Health & Wellbeing, University of Glasgow, Scotland, UK. Electronic address: a.ferguson.3@research.gla.ac.uk.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK; Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Neuroscience and Psychology, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Scotland, UK.; Big Data Institute, Nuffield Department of Population Health, BHF Centre of Research Excellence, University of Oxford, Oxford, UK; Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.; School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Scotland, UK.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK.; Department of Molecular and Cellular Therapeutics, Irish Centre for Vascular Biology, Royal College of Surgeons in Ireland (RCSI), Dublin, Ireland.; Institute of Health & Wellbeing, University of Glasgow, Scotland, UK. Electronic address: Daniel.Smith@glasgow.ac.uk.",EBioMedicine,2018,"BACKGROUND:Circadian rhythms are fundamental to health and are particularly important for mental wellbeing. Disrupted rhythms of rest and activity are recognised as risk factors for major depressive disorder and bipolar disorder. METHODS:We conducted a genome-wide association study (GWAS) of low relative amplitude (RA), an objective measure of rest-activity cycles derived from the accelerometer data of 71,500 UK Biobank participants. Polygenic risk scores (PRS) for low RA were used to investigate potential associations with psychiatric phenotypes. OUTCOMES:Two independent genetic loci were associated with low RA, within genomic regions for Neurofascin (NFASC) and Solute Carrier Family 25 Member 17 (SLC25A17). A secondary GWAS of RA as a continuous measure identified a locus within Meis Homeobox 1 (MEIS1). There were no significant genetic correlations between low RA and any of the psychiatric phenotypes assessed. However, PRS for low RA was significantly associated with mood instability across multiple PRS thresholds (at PRS threshold 0·05: OR = 1·02, 95% CI = 1·01-1·02, p = 9·6 × 10-5), and with major depressive disorder (at PRS threshold 0·1: OR = 1·03, 95% CI = 1·01-1·05, p = 0·025) and neuroticism (at PRS threshold 0·5: Beta = 0·02, 95% CI = 0·007-0·04, p = 0·021). INTERPRETATION:Overall, our findings contribute new knowledge on the complex genetic architecture of circadian rhythmicity and suggest a putative biological link between disrupted circadian function and mood disorder phenotypes, particularly mood instability, but also major depressive disorder and neuroticism. FUNDING:Medical Research Council (MR/K501335/1)."
 29925668,https://doi.org/10.1136/jech-2017-210370,Emergency hospital admissions associated with a non-randomised housing intervention meeting national housing quality standards: a longitudinal data linkage study.,"Rodgers SE, Bailey R, Johnson R, Berridge D, Poortinga W, Lannon S, Smith R, Lyons RA.","Department of Public Health and Policy, University of Liverpool, Liverpool, UK.; Health Data Research-UK, Swansea University, Swansea, UK.; Health Data Research-UK, Swansea University, Swansea, UK.; Health Data Research-UK, Swansea University, Swansea, UK.; Welsh School of Architecture, Cardiff University, Cardiff, Wales, UK.; Welsh School of Architecture, Cardiff University, Cardiff, Wales, UK.; School of Geography and Planning, Cardiff University, Cardiff, Wales, UK.; Health Data Research-UK, Swansea University, Swansea, UK.",Journal of epidemiology and community health,2018,"BACKGROUND:We investigated tenant healthcare utilisation associated with upgrading 8558 council houses to a national quality standard. Homes received multiple internal and external improvements and were analysed using repeated measures of healthcare utilisation. METHODS:The primary outcome was emergency hospital admissions for cardiorespiratory conditions and injuries for residents aged 60 years and over. Secondary outcomes included each of the separate conditions, for tenants aged 60 and over, and for all ages. Council home address and intervention records for eight housing cointerventions were anonymously linked to demographic data, hospital admissions and deaths for individuals in a dynamic cohort. Counts of health events were analysed using multilevel regression models to investigate associations between receipt of each housing improvement, adjusting for potential confounding factors and regional trends. RESULTS:Residents aged 60 years and over living in homes when improvements were made were associated with up to 39% fewer admissions compared with those living in homes that were not upgraded (incidence rate ratio=0.61, 95% CI 0.53 to 0.72). Reduced admissions were associated with electrical systems, windows and doors, wall insulation, and garden paths. There were small non-significant reductions for the primary outcome associated with upgrading heating, adequate loft insulation, new kitchens and new bathrooms. CONCLUSION:Results suggest that hospital admissions can be avoided through improving whole home quality standards. This is the first large-scale longitudinal evaluation of a whole home intervention that has evaluated multiple improvement elements using individual-level objective routine health data."
 30649175,https://doi.org/10.1001/jamacardio.2018.4537,Cardiovascular Risk Factors Associated With Venous Thromboembolism.,"Gregson J, Kaptoge S, Bolton T, Pennells L, Willeit P, Burgess S, Bell S, Sweeting M, Rimm EB, Kabrhel C, Zöller B, Assmann G, Gudnason V, Folsom AR, Arndt V, Fletcher A, Norman PE, Nordestgaard BG, Kitamura A, Mahmoodi BK, Whincup PH, Knuiman M, Salomaa V, Meisinger C, Koenig W, Kavousi M, Völzke H, Cooper JA, Ninomiya T, Casiglia E, Rodriguez B, Ben-Shlomo Y, Després JP, Simons L, Barrett-Connor E, Björkelund C, Notdurfter M, Kromhout D, Price J, Sutherland SE, Sundström J, Kauhanen J, Gallacher J, Beulens JWJ, Dankner R, Cooper C, Giampaoli S, Deen JF, Gómez de la Cámara A, Kuller LH, Rosengren A, Svensson PJ, Nagel D, Crespo CJ, Brenner H, Albertorio-Diaz JR, Atkins R, Brunner EJ, Shipley M, Njølstad I, Lawlor DA, van der Schouw YT, Selmer RM, Trevisan M, Verschuren WMM, Greenland P, Wassertheil-Smoller S, Lowe GDO, Wood AM, Butterworth AS, Thompson SG, Danesh J, Di Angelantonio E, Meade T, Emerging Risk Factors Collaboration.","London School of Hygiene and Tropical Medicine, London, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; Harvard T. H. Chan School of Public Health, Boston, Massachusetts.; Massachusetts General Hospital, Boston.; Department of Clinical Sciences, Lund University, Malmö, Sweden.; Assmann Foundation for Prevention, Münster, Germany.; Icelandic Heart Association, Kópavogur, Iceland.; University of Minnesota School of Public Health, Minneapolis.; Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.; London School of Hygiene and Tropical Medicine, London, United Kingdom.; University of Western Australia, Perth, Western Australia, Australia.; Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark.; Osaka University, Osaka, Japan.; University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.; St George's, University of London, London, United Kingdom.; University of Western Australia, Perth, Western Australia, Australia.; National Institute for Health and Welfare, Helsinki, Finland.; Ludwig Maximilian University of Munich, Munich, Germany.; Deutsches Herzzentrum München, Technische Universität München, Munich, Germany.; Erasmus University Medical Center, Erasmus University, Rotterdam, the Netherlands.; University of Greifswald, Greifswald, Germany.; UCL Medical School, University College London, London, United Kingdom.; Kyushu University, Fukuoka, Japan.; University of Padova, Padua, Italy.; University of Hawaii, Honolulu.; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; Institute of Nutraceuticals and Functional Foods, Université Laval, Quebec, Quebec, Canada.; The University of New South Wales, Sydney, New South Wales, Australia.; University of California, San Diego.; University of Gothenburg, Gothenburg, Sweden.; Department of Internal Medicine, Bruneck Hospital, Bruneck, Italy.; University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.; University of Edinburgh, Edinburgh, United Kingdom.; Medical University of South Carolina, Charleston.; University of Greifswald, Greifswald, Germany.; Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; VU University Medical Center Amsterdam, Amsterdam, the Netherlands.; Tel Aviv University, Tel Aviv, Israel.; MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom.; National Institute of Health (ISS), Rome, Italy.; Center of Health Equity, Diversity and Inclusion, University of Washington School of Medicine, Seattle.; Clinical Research and Clinical Trials Unit, Plataforma de Innovación en Tecnologías Médicas y Sanitarias, Madrid, Spain.; University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.; University of Gothenburg, Gothenburg, Sweden.; Department of Clinical Sciences, Lund University, Malmö, Sweden.; Ludwig Maximilian University of Munich, Munich, Germany.; Portland State University, Portland, Oregon.; University of Minnesota School of Public Health, Minneapolis.; US Centers for Disease Control and Prevention, Atlanta, Georgia.; Monash University, Melbourne, Victoria, Australia.; Department of Epidemiology and Public Health, University College London, London, United Kingdom.; Department of Epidemiology and Public Health, University College London, London, United Kingdom.; Norwegian Institute of Public Health, Oslo, Norway.; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Norwegian Institute of Public Health, Oslo, Norway.; CUNY School of Medicine, City University of New York, New York.; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Feinberg School of Medicine, Northwestern University, Chicago, Illinois.; Albert Einstein College of Medicine, New York, New York.; Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.; London School of Hygiene and Tropical Medicine, London, United Kingdom.",JAMA cardiology,2019,"Importance:It is uncertain to what extent established cardiovascular risk factors are associated with venous thromboembolism (VTE). Objective:To estimate the associations of major cardiovascular risk factors with VTE, ie, deep vein thrombosis and pulmonary embolism. Design, Setting, and Participants:This study included individual participant data mostly from essentially population-based cohort studies from the Emerging Risk Factors Collaboration (ERFC; 731 728 participants; 75 cohorts; years of baseline surveys, February 1960 to June 2008; latest date of follow-up, December 2015) and the UK Biobank (421 537 participants; years of baseline surveys, March 2006 to September 2010; latest date of follow-up, February 2016). Participants without cardiovascular disease at baseline were included. Data were analyzed from June 2017 to September 2018. Exposures:A panel of several established cardiovascular risk factors. Main Outcomes and Measures:Hazard ratios (HRs) per 1-SD higher usual risk factor levels (or presence/absence). Incident fatal outcomes in ERFC (VTE, 1041; coronary heart disease [CHD], 25 131) and incident fatal/nonfatal outcomes in UK Biobank (VTE, 2321; CHD, 3385). Hazard ratios were adjusted for age, sex, smoking status, diabetes, and body mass index (BMI). Results:Of the 731 728 participants from the ERFC, 403 396 (55.1%) were female, and the mean (SD) age at the time of the survey was 51.9 (9.0) years; of the 421 537 participants from the UK Biobank, 233 699 (55.4%) were female, and the mean (SD) age at the time of the survey was 56.4 (8.1) years. Risk factors for VTE included older age (ERFC: HR per decade, 2.67; 95% CI, 2.45-2.91; UK Biobank: HR, 1.81; 95% CI, 1.71-1.92), current smoking (ERFC: HR, 1.38; 95% CI, 1.20-1.58; UK Biobank: HR, 1.23; 95% CI, 1.08-1.40), and BMI (ERFC: HR per 1-SD higher BMI, 1.43; 95% CI, 1.35-1.50; UK Biobank: HR, 1.37; 95% CI, 1.32-1.41). For these factors, there were similar HRs for pulmonary embolism and deep vein thrombosis in UK Biobank (except adiposity was more strongly associated with pulmonary embolism) and similar HRs for unprovoked vs provoked VTE. Apart from adiposity, these risk factors were less strongly associated with VTE than CHD. There were inconsistent associations of VTEs with diabetes and blood pressure across ERFC and UK Biobank, and there was limited ability to study lipid and inflammation markers. Conclusions and Relevance:Older age, smoking, and adiposity were consistently associated with higher VTE risk."
+30351417,https://doi.org/10.1093/bioinformatics/bty837,pJRES Binning Algorithm (JBA): a new method to facilitate the recovery of metabolic information from pJRES 1H NMR spectra.,"Rodriguez-Martinez A, Ayala R, Posma JM, Harvey N, Jiménez B, Sonomura K, Sato TA, Matsuda F, Zalloua P, Gauguier D, Nicholson JK, Dumas ME.","Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, Imperial College London, London, UK.; Section of Structural Biology, Department of Medicine, Shimadzu Corporation, Kyoto, Japan.; Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, Imperial College London, London, UK.; Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, Imperial College London, London, UK.; Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, Imperial College London, London, UK.; Life Science Research Center, Technology Research Laboratory, Shimadzu Corporation, Kyoto, Japan.; Life Science Research Center, Technology Research Laboratory, Shimadzu Corporation, Kyoto, Japan.; Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.; School of Medicine, Lebanese American University, Beirut, Lebanon.; Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.; Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, Imperial College London, London, UK.; Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, Imperial College London, London, UK.","Bioinformatics (Oxford, England)",2019,"MOTIVATION:Data processing is a key bottleneck for 1H NMR-based metabolic profiling of complex biological mixtures, such as biofluids. These spectra typically contain several thousands of signals, corresponding to possibly few hundreds of metabolites. A number of binning-based methods have been proposed to reduce the dimensionality of 1 D 1H NMR datasets, including statistical recoupling of variables (SRV). Here, we introduce a new binning method, named JBA (""pJRES Binning Algorithm""), which aims to extend the applicability of SRV to pJRES spectra. RESULTS:The performance of JBA is comprehensively evaluated using 617 plasma 1H NMR spectra from the FGENTCARD cohort. The results presented here show that JBA exhibits higher sensitivity than SRV to detect peaks from low-abundance metabolites. In addition, JBA allows a more efficient removal of spectral variables corresponding to pure electronic noise, and this has a positive impact on multivariate model building. AVAILABILITY AND IMPLEMENTATION:The algorithm is implemented using the MWASTools R/Bioconductor package. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online."
+31101093,https://doi.org/10.1186/s12889-019-6888-9,Educational and health outcomes of children and adolescents receiving antiepileptic medication: Scotland-wide record linkage study of 766 244 schoolchildren.,"Fleming M, Fitton CA, Steiner MFC, McLay JS, Clark D, King A, Mackay DF, Pell JP.","Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK. michael.fleming@glasgow.ac.uk.; Department of Child Health, University of Aberdeen, Aberdeen, AB25 2ZG, UK.; Department of Child Health, University of Aberdeen, Aberdeen, AB25 2ZG, UK.; Department of Child Health, University of Aberdeen, Aberdeen, AB25 2ZG, UK.; Information Services Division, Edinburgh, EH12 9EB, UK.; ScotXed, Scottish Government, Edinburgh, EH6 6QQ, UK.; Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK.; Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK.",BMC public health,2019,"BACKGROUND:Childhood epilepsy can adversely affect education and employment in addition to health. Previous studies are small or highly selective producing conflicting results. This retrospective cohort study aims to compare educational and health outcomes of children receiving antiepileptic medication versus peers. METHODS:Record linkage of Scotland-wide databases covering dispensed prescriptions, acute and psychiatric hospitalisations, maternity records, deaths, annual pupil census, school absences/exclusions, special educational needs, school examinations, and (un)employment provided data on 766,244 children attending Scottish schools between 2009 and 2013. Outcomes were adjusted for sociodemographic and maternity confounders and comorbid conditions. RESULTS:Compared with peers, children on antiepileptic medication were more likely to experience school absence (Incidence Rate Ratio [IRR] 1.43, 95% CI: 1.38, 1.48), special educational needs (Odds ratio [OR] 9.60, 95% CI: 9.02, 10.23), achieve the lowest level of attainment (OR 3.43, 95% CI: 2.74, 4.29) be unemployed (OR 1.82, 95% CI: 1.60, 2.07), be admitted to hospital (Hazard Ratio [HR] 3.56, 95% CI: 3.42, 3.70), and die (HR 22.02, 95% CI: 17.00, 28.53). Absenteeism partly explained poorer attainment and higher unemployment. Girls and younger children on antiepileptic medication had higher risk of poor outcomes. CONCLUSIONS:Children on antiepileptic medication fare worse than peers across educational and health outcomes. In order to reduce school absenteeism and mitigate its effects, children with epilepsy should receive integrated care from a multidisciplinary team that spans education and healthcare."
 30984759,https://doi.org/10.3389/fmed.2019.00048,"Direct-to-Consumer Genetic Testing's Red Herring: ""Genetic Ancestry"" and Personalized Medicine.","Blell M, Hunter MA.","Policy, Ethics and Life Sciences Research Centre, School of Geography, Politics and Sociology, Newcastle University, Newcastle-upon-Tyne, United Kingdom.; Department of Philosophy, Logic, and Scientific Method, Centre for Philosophy of Natural and Social Science (CPNSS), The London School of Economics and Political Science, London, United Kingdom.",Frontiers in medicine,2019,"The growth in the direct-to-consumer genetic testing industry poses a number of challenges for healthcare practice, among a number of other areas of concern. Several companies providing this service send their customers reports including information variously referred to as genetic ethnicity, genetic heritage, biogeographic ancestry, and genetic ancestry. In this article, we argue that such information should not be used in healthcare consultations or to assess health risks. Far from representing a move toward personalized medicine, use of this information poses risks both to patients as individuals and to racialized ethnic groups because of the way it misrepresents human genetic diversity."
 31073125,https://doi.org/10.1038/s41533-019-0132-z,Systematic review of clinical prediction models to support the diagnosis of asthma in primary care.,"Daines L, McLean S, Buelo A, Lewis S, Sheikh A, Pinnock H.","Asthma UK Centre for Applied Research, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK. luke.daines@ed.ac.uk.; Asthma UK Centre for Applied Research, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.; Scottish Collaboration for Public Health Research and Policy, The University of Edinburgh, Edinburgh, UK.; Edinburgh Clinical Trials Unit, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.; Asthma UK Centre for Applied Research, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.; Asthma UK Centre for Applied Research, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK.",NPJ primary care respiratory medicine,2019,"Diagnosing asthma is challenging. Misdiagnosis can lead to untreated symptoms, incorrect treatment and avoidable deaths. The best combination of clinical features and tests to achieve a diagnosis of asthma is unclear. As asthma is usually diagnosed in non-specialist settings, a clinical prediction model to aid the assessment of the probability of asthma in primary care may improve diagnostic accuracy. We aimed to identify and describe existing prediction models to support the diagnosis of asthma in children and adults in primary care. We searched Medline, Embase, CINAHL, TRIP and US National Guidelines Clearinghouse databases from 1 January 1990 to 23 November 17. We included prediction models designed for use in primary care or equivalent settings to aid the diagnostic decision-making of clinicians assessing patients with symptoms suggesting asthma. Two reviewers independently screened titles, abstracts and full texts for eligibility, extracted data and assessed risk of bias. From 13,798 records, 53 full-text articles were reviewed. We included seven modelling studies; all were at high risk of bias. Model performance varied, and the area under the receiving operating characteristic curve ranged from 0.61 to 0.82. Patient-reported wheeze, symptom variability and history of allergy or allergic rhinitis were associated with asthma. In conclusion, clinical prediction models may support the diagnosis of asthma in primary care, but existing models are at high risk of bias and thus unreliable for informing practice. Future studies should adhere to recognised standards, conduct model validation and include a broader range of clinical data to derive a prediction model of value for clinicians."
 30772400,https://doi.org/10.1016/j.neuroimage.2019.02.028,Hierarchical complexity of the adult human structural connectome.,"Smith K, Bastin ME, Cox SR, Valdés Hernández MC, Wiseman S, Escudero J, Sudlow C.","Usher Institute for Population Health Science and Informatics, Medical School, University of Edinburgh, Edinburgh, EH16 4UX, UK. Electronic address: k.smith@ed.ac.uk.; Centre for Clinical Brain Sciences, Western General Hospital, University of Edinburgh, Edinburgh, EH4 2XU, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.; Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.; Centre for Clinical Brain Sciences, Western General Hospital, University of Edinburgh, Edinburgh, EH4 2XU, UK; Row Fogo Centre into Ageing and the Brain, Edinburgh Dementia Research Institute, University of Edinburgh, Edinburgh, EH16 4SB, UK.; Centre for Clinical Brain Sciences, Western General Hospital, University of Edinburgh, Edinburgh, EH4 2XU, UK.; School of Engineering, Institute for Digital Communications, University of Edinburgh, Edinburgh, EH9 3FB, UK.; Usher Institute for Population Health Science and Informatics, Medical School, University of Edinburgh, Edinburgh, EH16 4UX, UK.",NeuroImage,2019,"The structural network of the human brain has a rich topology which many have sought to characterise using standard network science measures and concepts. However, this characterisation remains incomplete and the non-obvious features of this topology have largely confounded attempts towards comprehensive constructive modelling. This calls for new perspectives. Hierarchical complexity is an emerging paradigm of complex network topology based on the observation that complex systems are composed of hierarchies within which the roles of hierarchically equivalent nodes display highly variable connectivity patterns. Here we test the hierarchical complexity of the human structural connectomes of a group of seventy-nine healthy adults. Binary connectomes are found to be more hierarchically complex than three benchmark random network models. This provides a new key description of brain structure, revealing a rich diversity of connectivity patterns within hierarchically equivalent nodes. Dividing the connectomes into four tiers based on degree magnitudes indicates that the most complex nodes are neither those with the highest nor lowest degrees but are instead found in the middle tiers. Spatial mapping of the brain regions in each hierarchical tier reveals consistency with the current anatomical, functional and neuropsychological knowledge of the human brain. The most complex tier (Tier 3) involves regions believed to bridge high-order cognitive (Tier 1) and low-order sensorimotor processing (Tier 2). We then show that such diversity of connectivity patterns aligns with the diversity of functional roles played out across the brain, demonstrating that hierarchical complexity can characterise functional diversity strictly from the network topology."
+31171806,https://doi.org/10.1038/s41598-019-44907-8,On neighbourhood degree sequences of complex networks.,Smith KM.,"Usher Institute of Population Health Science and Informatics, University of Edinburgh, 9 BioQuarter, Little France, Edinburgh, EH16 4UX, UK. k.smith@ed.ac.uk.",Scientific reports,2019,"Network topology is a fundamental aspect of network science that allows us to gather insights into the complicated relational architectures of the world we inhabit. We provide a first specific study of neighbourhood degree sequences in complex networks. We consider how to explicitly characterise important physical concepts such as similarity, heterogeneity and organization in these sequences, as well as updating the notion of hierarchical complexity to reflect previously unnoticed organizational principles. We also point out that neighbourhood degree sequences are related to a powerful subtree kernel for unlabeled graph classification. We study these newly defined sequence properties in a comprehensive array of graph models and over 200 real-world networks. We find that these indices are neither highly correlated with each other nor with classical network indices. Importantly, the sequences of a wide variety of real world networks are found to have greater similarity and organisation than is expected for networks of their given degree distributions. Notably, while biological, social and technological networks all showed consistently large neighbourhood similarity and organisation, hierarchical complexity was not a consistent feature of real world networks. Neighbourhood degree sequences are an interesting tool for describing unique and important characteristics of complex networks."
 30921401,https://doi.org/10.1371/journal.pone.0214607,Effect of impregnated central venous catheters on thrombosis in paediatric intensive care: Post-hoc analyses of the CATCH trial.,"Wu Y, Fraser C, Gilbert R, Mok Q.","University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom.; Population, Policy and Practice Programme, NIHR Biomedical Research Centre, University College London Great Ormond Street Institute of Child Health, London, United Kingdom.; Population, Policy and Practice Programme, NIHR Biomedical Research Centre, University College London Great Ormond Street Institute of Child Health, London, United Kingdom.; Paediatric Intensive Care Unit, Great Ormond Street Hospital for Children, London, United Kingdom.",PloS one,2019,"PURPOSE:The CATheter infections in CHildren (CATCH) trial reported reduced risks of bloodstream infection with antibiotic impregnated compared with heparin-bonded or standard central venous catheters (CVC) in paediatric intensive care. CVC impregnation did not increase the risk of thrombosis which was recorded in 24% of participants. This post-hoc analysis determines the effect of CVC impregnation on the risk of thrombosis leading to CVC removal or swollen limb. METHODS:We analysed patients in the CATCH trial, blind to CVC allocation, to define clinically relevant thrombosis based on the clinical sign most frequently recorded in patients where the CVC was removed because of concerns regarding thrombosis. In post-hoc, three-way comparisons of antibiotic, heparin and standard CVCs, we determined the effect of CVC type on time to clinically relevant thrombosis, using Cox proportional hazards regression. RESULTS:Of 1409 participants with a successful CVC insertion, the sign most frequently resulting in CVC removal was swollen limb (37.6%; 41/109), with lower rates of removal of CVC following 2 episodes of difficulty withdrawing blood or of flushing to unblock the CVC. In intention to treat analyses (n = 1485), clinically relevant thrombosis, defined by 1 or more record of swollen limb or CVC removal due to concerns about thrombosis, was recorded in 11.9% (58/486) of antibiotic CVCs, 12.1% (60/497) of heparin CVCs, and 10.2% (51/502) of standard CVCs. We found no differences in time to clinically relevant thrombosis according to type of CVC. CONCLUSIONS:We found no evidence for an increased risk of clinically relevant thrombosis in antibiotic impregnated compared to heparin-bonded or standard CVCs in children receiving intensive care."
 30835202,https://doi.org/10.7554/eLife.43657,An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome.,"Richardson TG, Harrison S, Hemani G, Davey Smith G.","MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.",eLife,2019,"The age of large-scale genome-wide association studies (GWAS) has provided us with an unprecedented opportunity to evaluate the genetic liability of complex disease using polygenic risk scores (PRS). In this study, we have analysed 162 PRS (p<5×10-05) derived from GWAS and 551 heritable traits from the UK Biobank study (N = 334,398). Findings can be investigated using a web application (http:‌//‌mrcieu.‌mrsoftware.org/‌PRS‌_atlas/), which we envisage will help uncover both known and novel mechanisms which contribute towards disease susceptibility. To demonstrate this, we have investigated the results from a phenome-wide evaluation of schizophrenia genetic liability. Amongst findings were inverse associations with measures of cognitive function which extensive follow-up analyses using Mendelian randomization (MR) provided evidence of a causal relationship. We have also investigated the effect of multiple risk factors on disease using mediation and multivariable MR frameworks. Our atlas provides a resource for future endeavours seeking to unravel the causal determinants of complex disease."
+30729733,https://doi.org/10.1111/ijpo.12512,Predictors of objectively measured physical activity in 12-month-old infants: A study of linked birth cohort data with electronic health records.,"Raza H, Zhou SM, Todd C, Christian D, Marchant E, Morgan K, Khanom A, Hill R, Lyons RA, Brophy S.","The School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Department of Sport and Physical Activity, Edge Hill University, Ormskirk, UK.; Health Data Research UK, Swansea University, Swansea, UK.; DECIPHer, School of Social Sciences, Cardiff University, Cardiff, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Abertawe Bro Morgannwg University Health Board (ABM UHB), Port Talbot, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.",Pediatric obesity,2019,"BACKGROUND:Physical activity (PA) levels are associated with long-term health, and levels of PA when young are predictive of adult activity levels. OBJECTIVES:This study examines factors associated with PA levels in 12-month infants. METHOD:One hundred forty-one mother-infant pairs were recruited via a longitudinal birth cohort study (April 2010 to March 2013). The PA level was collected using accelerometers and linked to postnatal notes and electronic medical records via the Secure Anonymised Information Linkage databank. Univariable and multivariable linear regressions were used to examine the factors associated with PA levels. RESULTS:Using univariable analysis, higher PA was associated with the following (P value less than 0.05): being male, larger infant size, healthy maternal blood pressure levels, full-term gestation period, higher consumption of vegetables (infant), lower consumption of juice (infant), low consumption of adult crisps (infant), longer breastfeeding duration, and more movement during sleep (infant) but fewer night wakings. Combined into a multivariable regression model (R2  = 0.654), all factors remained significant, showing lower PA levels were associated with female gender, smaller infant, preterm birth, higher maternal blood pressure, low vegetable consumption, high crisp consumption, and less night movement. CONCLUSION:The PA levels of infants were strongly associated with both gestational and postnatal environmental factors. Healthy behaviours appear to cluster, and a healthy diet was associated with a more active infant. Boys were substantially more active than girls, even at age 12 months. These findings can help inform interventions to promote healthier lives for infants and to understand the determinants of their PA levels."
+30659777,https://doi.org/10.1111/ijpo.12505,Are children with clinical obesity at increased risk of inpatient hospital admissions? An analysis using linked electronic health records in the UK millennium cohort study.,"Griffiths LJ, Cortina-Borja M, Bandyopadhyay A, Tingay K, De Stavola BL, Bedford H, Akbari A, Firman N, Lyons RA, Dezateux C.","Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; National Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, UK.; Administrative Data Research Centre Wales, Swansea University Medical School, Swansea, UK.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.",Pediatric obesity,2019,"BACKGROUND:Few studies have examined health service utilization of children with overweight or obesity by using linked electronic health records (EHRs). OBJECTIVE/METHODS:We analysed EHRs from 3269 children (1678 boys; 51.3% [weighted]) participating in the Millennium Cohort Study, living in Wales or Scotland at age seven whose parents consented to record linkage. We used height and weight measurements at age five to categorize children as obese (>98th centile) or overweight (>91st centile) (UK1990 clinical reference standards) and linked to hospital admissions, up to age 14 years, in the Patient Episode Database for Wales and Scottish Morbidity Records. Negative binomial regression models compared rates of inpatient admissions by weight status at age five. RESULTS:At age five, 11.5% and 6.7% of children were overweight or obese, respectively; 1221 (38%) children were subsequently admitted to hospital at least once. Admissions were not increased among children with overweight or obesity (adjusted rate ratio [RR], 95% confidence interval [CI]: 0.87, 0.68-1.10 and 1.16, 0.87-1.54, respectively). CONCLUSIONS:In this nationally representative cohort of children in Wales and Scotland, those with overweight or obesity at entry to primary school did not have increased rates of hospital admissions in later childhood and early adolescence."
+31220083,https://doi.org/10.1371/journal.pmed.1002833,Associations of genetically determined iron status across the phenome: A mendelian randomization study.,"Gill D, Benyamin B, Moore LSP, Monori G, Zhou A, Koskeridis F, Evangelou E, Laffan M, Walker AP, Tsilidis KK, Dehghan A, Elliott P, Hyppönen E, Tzoulaki I.","Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Australian Centre for Precision Health, University of South Australia, Adelaide, Australia.; National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Australian Centre for Precision Health, University of South Australia, Adelaide, Australia.; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Centre for Haematology, Imperial College London, United Kingdom.; Population Science & Experimental Medicine, Institute of Cardiovascular Science, University College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.; Australian Centre for Precision Health, University of South Australia, Adelaide, Australia.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.",PLoS medicine,2019,"BACKGROUND:Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status. METHODS AND FINDINGS:Genome-wide association study (GWAS) summary data obtained from 48,972 European individuals (55% female) across 19 cohorts in the Genetics of Iron Status Consortium were used to identify 3 genetic variants (rs1800562 and rs1799945 in the hemochromatosis gene [HFE] and rs855791 in the transmembrane protease serine 6 gene [TMPRSS6]) that associate with increased serum iron, ferritin, and transferrin saturation and decreased transferrin levels, thus serving as instruments for systemic iron status. Phenome-wide association study (PheWAS) of these instruments was performed on 424,439 European individuals (54% female) in the UK Biobank who were aged 40-69 years when recruited from 2006 to 2010, with their genetic data linked to Hospital Episode Statistics (HES) from April, 1995 to March, 2016. Two-sample summary data mendelian randomization (MR) analysis was performed to investigate the effect of varying iron status on outcomes across the human phenome. MR-PheWAS analysis for the 3 iron status genetic instruments was performed separately and then pooled by meta-analysis. Correction was made for testing of multiple correlated phenotypes using a 5% false discovery rate (FDR) threshold. Heterogeneity between MR estimates for different instruments was used to indicate possible bias due to effects of the genetic variants through pathways unrelated to iron status. There were 904 distinct phenotypes included in the MR-PheWAS analyses. After correcting for multiple testing, the 3 genetic instruments for systemic iron status demonstrated consistent evidence of a causal effect of higher iron status on decreasing risk of traits related to anemia (iron deficiency anemia: odds ratio [OR] scaled to a standard deviation [SD] increase in genetically determined serum iron levels 0.72, 95% confidence interval [CI] 0.64-0.81, P = 4 × 10-8) and hypercholesterolemia (hypercholesterolemia: OR 0.88, 95% CI 0.83-0.93, P = 2 × 10-5) and increasing risk of traits related to infection of the skin and related structures (cellulitis and abscess of the leg: OR 1.25, 95% CI 1.10-1.42, P = 6 × 10-4). The main limitations of this study relate to possible bias from pleiotropic effects of the considered genetic variants and misclassification of diagnoses in the HES data. Furthermore, this work only investigated participants with European ancestry, and the findings may not be applicable to other ethnic groups. CONCLUSIONS:Our findings offer novel, to our knowledge, insight into previously unreported effects of iron status, highlighting a potential protective effect of higher iron status on hypercholesterolemia and a detrimental role on risk of skin and skin structure infections. Given the modifiable and variable nature of iron status, these findings warrant further investigation."
+31115347,https://doi.org/10.2196/12412,Health Data Processes: A Framework for Analyzing and Discussing Efficient Use and Reuse of Health Data With a Focus on Patient-Reported Outcome Measures.,"Hjollund NHI, Valderas JM, Kyte D, Calvert MJ.","Occupational Medicine, University Research Clinic, AmbuFlex/WestChronic, Aarhus University, Herning, Denmark.; University of Exeter Collaboration for Academic Primary Care, Health Services & Policy Research Group, National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care (South West Peninsula), University of Exeter, Exeter, United Kingdom.; Centre for Patient Reported Outcomes Research, Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham, United Kingdom.; Centre for Patient Reported Outcomes Research, Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham, United Kingdom.",Journal of medical Internet research,2019,"The collection and use of patient health data are central to any kind of activity in the health care system. These data may be produced during routine clinical processes or obtained directly from the patient using patient-reported outcome (PRO) measures. Although efficiency and other reasons justify data availability for a range of potentially relevant uses, these data are nearly always collected for a single specific purpose. The health care literature reflects this narrow scope, and there is limited literature on the joint use of health data for daily clinical use, clinical research, surveillance, and administrative purposes. The aim of this paper is to provide a framework for discussing the efficient use of health data with a specific focus on the role of PRO measures. PRO data may be used at an individual patient level to inform patient care or shared decision making and to tailor care to individual needs or group-level needs as a complement to health record data, such as that on mortality and readmission, in order to inform service delivery and measure the real-world effectiveness of treatment. PRO measures may be used either for their own sake, to provide valuable information from the patient perspective, or as a proxy for clinical data that would otherwise not be feasible to collect. We introduce a framework to analyze any health care activity that involves health data. The framework consists of four data processes (patient identification, data collection, data aggregation and data use), further structured into two dichotomous dimensions in each data process (level: group vs patient; timeframe: ad hoc vs systematic). This framework is used to analyze various health activities with respect to joint use of data, considering the technical, legal, organizational, and logistical challenges that characterize each data process. Finally, we propose a model for joint use of health data with data collected during follow-up as a base. Demands for health data will continue to increase, which will further add to the need for the concerted use and reuse of PRO data for parallel purposes. Repeated and uncoordinated PRO data collection for the same patient for different purposes results in misuse of resources for the patient and the health care system as well as reduced response rates owing to questionnaire fatigue. PRO data can be routinely collected both at the hospital (from inpatients as well as outpatients) and outside of hospital settings; in primary or social care settings; or in the patient's home, provided the health informatics infrastructure is in place. In the future, clinical settings are likely to be a prominent source of PRO data; however, we are also likely to see increased remote collection of PRO data by patients in their own home (telePRO). Data collection for research and quality surveillance will have to adapt to this circumstance and adopt complementary data capture methods that take advantage of the utility of PRO data collected during daily clinical practice. The European Union's regulation with respect to the protection of personal data-General Data Protection Regulation-imposes severe restrictions on the use of health data for parallel purposes, and steps should be taken to alleviate the consequences while still protecting personal data against misuse."
 30183734,https://doi.org/10.1371/journal.pone.0202359,Time spent at blood pressure target and the risk of death and cardiovascular diseases.,"Chung SC, Pujades-Rodriguez M, Duyx B, Denaxas SC, Pasea L, Hingorani A, Timmis A, Williams B, Hemingway H.","Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.; Institute of Cardiovascular Science, University College London, London, United Kingdom.; Health Data Research UK London, University College London, London, United Kingdom.",PloS one,2018,"BACKGROUND:The time a patient spends with blood pressure at target level is an intuitive measure of successful BP management, but population studies on its effectiveness are as yet unavailable. METHOD:We identified a population-based cohort of 169,082 individuals with newly identified high blood pressure who were free of cardiovascular disease from January 1997 to March 2010. We used 1.64 million clinical blood pressure readings to calculate the TIme at TaRgEt (TITRE) based on current target blood pressure levels. RESULT:The median (Inter-quartile range) TITRE among all patients was 2.8 (0.3, 5.6) months per year, only 1077 (0.6%) patients had a TITRE ≥11 months. Compared to people with a 0% TITRE, patients with a TITRE of 3-5.9 months, and 6-8.9 months had 75% and 78% lower odds of the composite of cardiovascular death, myocardial infarction and stroke (adjusted odds ratios, 0.25 (95% confidence interval: 0.21, 0.31) and 0.22 (0.17, 0.27), respectively). These associations were consistent for heart failure and any cardiovascular disease and death (comparing a 3-5.9 month to 0% TITRE, 63% and 60% lower in odds, respectively), among people who did or did not have blood pressure 'controlled' on a single occasion during the first year of follow-up, and across groups defined by number of follow-up BP measure categories. CONCLUSION:Based on the current frequency of measurement of blood pressure this study suggests that few newly hypertensive patients sustained a complete, year-round on target blood pressure over time. The inverse associations between a higher TITRE and lower risk of incident cardiovascular diseases were independent of widely-used blood pressure 'control' indicators. Randomized trials are required to evaluate interventions to increase a person's time spent at blood pressure target."
 30774489,https://doi.org/10.2147/PROM.S162802,The use of patient-reported outcome research in modern ophthalmology: impact on clinical trials and routine clinical practice.,"Braithwaite T, Calvert M, Gray A, Pesudovs K, Denniston AK.","Centre for Patient Reported Outcomes Research and NIHR Birmingham Biomedical Research Centre, University of Birmingham, Edgbaston, Birmingham, UK, tasaneebraithwaite@gmail.com.; Centre for Patient Reported Outcomes Research and NIHR Birmingham Biomedical Research Centre, University of Birmingham, Edgbaston, Birmingham, UK, tasaneebraithwaite@gmail.com.; Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Consultant, Adelaide, SA, Australia.; Centre for Patient Reported Outcomes Research and NIHR Birmingham Biomedical Research Centre, University of Birmingham, Edgbaston, Birmingham, UK, tasaneebraithwaite@gmail.com.",Patient related outcome measures,2019,"This review article considers the rising demand for patient-reported outcome measures (PROMs) in modern ophthalmic research and clinical practice. We review what PROMs are, how they are developed and chosen for use, and how their quality can be critically appraised. We outline the progress made to develop PROMs in each clinical subspecialty. We highlight recent examples of the use of PROMs as secondary outcome measures in randomized controlled clinical trials and consider the impact they have had. With increasing interest in using PROMs as primary outcome measures, particularly where interventions have been found to be of equivalent efficacy by traditional outcome metrics, we highlight the importance of instrument precision in permitting smaller sample sizes to be recruited. Our review finds that while there has been considerable progress in PROM development, particularly in cataract, glaucoma, medical retina, and low vision, there is a paucity of useful tools for less common ophthalmic conditions. Development and validation of item banks, administered using computer adaptive testing, has been proposed as a solution to overcome many of the traditional limitations of PROMs, but further work will be needed to examine their acceptability to patients, clinicians, and investigators."
 30909231,https://doi.org/10.3233/JAD-181085,A Meta-Analysis of Alzheimer's Disease Brain Transcriptomic Data.,"Patel H, Dobson RJB, Newhouse SJ.","Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.",Journal of Alzheimer's disease : JAD,2019,"BACKGROUND:Microarray technologies have identified imbalances in the expression of specific genes and biological pathways in Alzheimer's disease (AD) brains. However, there is a lack of reproducibility across individual AD studies, and many related neurodegenerative and mental health disorders exhibit similar perturbations. OBJECTIVE:Meta-analyze publicly available transcriptomic data from multiple brain-related disorders to identify robust transcriptomic changes specific to AD brains. METHODS:Twenty-two AD, eight schizophrenia, five bipolar disorder, four Huntington's disease, two major depressive disorder, and one Parkinson's disease dataset totaling 2,667 samples and mapping to four different brain regions (temporal lobe, frontal lobe, parietal lobe, and cerebellum) were analyzed. Differential expression analysis was performed independently in each dataset, followed by meta-analysis using a combining p-value method known as Adaptively Weighted with One-sided Correction. RESULTS:Meta-analysis identified 323, 435, 1,023, and 828 differentially expressed genes specific to the AD temporal lobe, frontal lobe, parietal lobe, and cerebellum brain regions, respectively. Seven of these genes were consistently perturbed across all AD brain regions with SPCS1 gene expression pattern replicating in RNA-Seq data. A further nineteen genes were perturbed specifically in AD brain regions affected by both plaques and tangles, suggesting possible involvement in AD neuropathology. In addition, biological pathways involved in the ""metabolism of proteins"" and viral components were significantly enriched across AD brains. CONCLUSION:This study identified transcriptomic changes specific to AD brains, which could make a significant contribution toward the understanding of AD disease mechanisms and may also provide new therapeutic targets."
+31122927,https://doi.org/10.1136/bmj.l1778,Determinants of the decline in mortality from acute stroke in England: linked national database study of 795 869 adults.,"Seminog OO, Scarborough P, Wright FL, Rayner M, Goldacre MJ.","Unit of Health-Care Epidemiology, Big Data Institute, Nuffield Department of Population Health, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford OX3 7LF, UK olena.seminog@ndph.ox.ac.uk.; Centre on Population Approaches for Non-communicable Disease Prevention, Nuffield Department of Population Health, NIHR Biomedical Research Centre at Oxford, University of Oxford, Oxford, UK.; Unit of Health-Care Epidemiology, Big Data Institute, Nuffield Department of Population Health, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford OX3 7LF, UK.; Centre on Population Approaches for Non-communicable Disease Prevention, Nuffield Department of Population Health, NIHR Biomedical Research Centre at Oxford, University of Oxford, Oxford, UK.; Unit of Health-Care Epidemiology, Big Data Institute, Nuffield Department of Population Health, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford OX3 7LF, UK.",BMJ (Clinical research ed.),2019,"OBJECTIVES:To study trends in stroke mortality rates, event rates, and case fatality, and to explain the extent to which the reduction in stroke mortality rates was influenced by changes in stroke event rates or case fatality. DESIGN:Population based study. SETTING:Person linked routine hospital and mortality data, England. PARTICIPANTS:795 869 adults aged 20 and older who were admitted to hospital with acute stroke or died from stroke. MAIN OUTCOME MEASURES:Stroke mortality rates, stroke event rates (stroke admission or stroke death without admission), and case fatality within 30 days after stroke. RESULTS:Between 2001 and 2010 stroke mortality rates decreased by 55%, stroke event rates by 20%, and case fatality by 40%. The study population included 358 599 (45%) men and 437 270 (55%) women. Average annual change in mortality rate was -6.0% (95% confidence interval -6.2% to -5.8%) in men and -6.1% (-6.3% to -6.0%) in women, in stroke event rate was -1.3% (-1.4% to -1.2%) in men and -2.1% (-2.2 to -2.0) in women, and in case fatality was -4.7% (-4.9% to -4.5%) in men and -4.4% (-4.5% to -4.2%) in women. Mortality and case fatality but not event rate declined in all age groups: the stroke event rate decreased in older people but increased by 2% each year in adults aged 35 to 54 years. Of the total decline in mortality rates, 71% was attributed to the decline in case fatality (78% in men and 66% in women) and the remainder to the reduction in stroke event rates. The contribution of the two factors varied between age groups. Whereas the reduction in mortality rates in people younger than 55 years was due to the reduction in case fatality, in the oldest age group (≥85 years) reductions in case fatality and event rates contributed nearly equally. CONCLUSIONS:Declines in case fatality, probably driven by improvements in stroke care, contributed more than declines in event rates to the overall reduction in stroke mortality. Mortality reduction in men and women younger than 55 was solely a result of a decrease in case fatality, whereas stroke event rates increased in the age group 35 to 54 years. The increase in stroke event rates in young adults is a concern. This suggests that stroke prevention needs to be strengthened to reduce the occurrence of stroke in people younger than 55 years."
+31005938,https://doi.org/10.1136/bmjopen-2018-027289,"Longitudinal access and exposure to green-blue spaces and individual-level mental health and well-being: protocol for a longitudinal, population-wide record-linked natural experiment.","Mizen A, Song J, Fry R, Akbari A, Berridge D, Parker SC, Johnson R, Lovell R, Lyons RA, Nieuwenhuijsen M, Stratton G, Wheeler BW, White J, White M, Rodgers SE.","Swansea University Medical School, Swansea University, Swansea, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; European Centre for Environment and Human Health, University of Exeter Medical School, Knowledge Spa, Royal Cornwall Hospital, Cornwall, UK.; Swansea University Medical School, Swansea University, Swansea, UK.; Instituto de Salud Global de Barcelona.c/ Rosselló, 132, 5º 2ª, Barcelona, Spain.; Research Centre in Applied Sports, Technology Exercise and Medicine, College of Engineering, Swansea University, Swansea, UK.; European Centre for Environment and Human Health, University of Exeter Medical School, Knowledge Spa, Royal Cornwall Hospital, Cornwall, UK.; DECIPHer, Centre for Trials Research, Cardiff University, Cardiff, UK.; European Centre for Environment and Human Health, University of Exeter Medical School, Knowledge Spa, Royal Cornwall Hospital, Cornwall, UK.; Swansea University Medical School, Swansea University, Swansea, UK.",BMJ open,2019,"INTRODUCTION:Studies suggest that access and exposure to green-blue spaces (GBS) have beneficial impacts on mental health. However, the evidence base is limited with respect to longitudinal studies. The main aim of this longitudinal, population-wide, record-linked natural experiment, is to model the daily lived experience by linking GBS accessibility indices, residential GBS exposure and health data; to enable quantification of the impact of GBS on well-being and common mental health disorders, for a national population. METHODS AND ANALYSIS:This research will estimate the impact of neighbourhood GBS access, GBS exposure and visits to GBS on the risk of common mental health conditions and the opportunity for promoting subjective well-being (SWB); both key priorities for public health. We will use a Geographic Information System (GIS) to create quarterly household GBS accessibility indices and GBS exposure using digital map and satellite data for 1.4 million homes in Wales, UK (2008-2018). We will link the GBS accessibility indices and GBS exposures to individual-level mental health outcomes for 1.7 million people with general practitioner (GP) data and data from the National Survey for Wales (n=~12 000) on well-being in the Secure Anonymised Information Linkage (SAIL) Databank. We will examine if these associations are modified by multiple sociophysical variables, migration and socioeconomic disadvantage. Subgroup analyses will examine associations by different types of GBS. This longitudinal study will be augmented by cross-sectional research using survey data on self-reported visits to GBS and SWB. ETHICS AND DISSEMINATION:All data will be anonymised and linked within the privacy protecting SAIL Databank. We will be using anonymised data and therefore we are exempt from National Research Ethics Committee (NREC). An Information Governance Review Panel (IGRP) application (Project ID: 0562) to link these data has been approved.The research programme will be undertaken in close collaboration with public/patient involvement groups. A multistrategy programme of dissemination is planned with the academic community, policy-makers, practitioners and the public."
 30999919,https://doi.org/10.1186/s12911-019-0805-0,Identifying clinically important COPD sub-types using data-driven approaches in primary care population based electronic health records.,"Pikoula M, Quint JK, Nissen F, Hemingway H, Smeeth L, Denaxas S.","Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK. m.pikoula@ucl.ac.uk.; Health Data Research UK London, University College London, 222 Euston Road, London, NW1 2DA, UK.; Health Data Research UK London, University College London, 222 Euston Road, London, NW1 2DA, UK.; Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK.; Health Data Research UK London, University College London, 222 Euston Road, London, NW1 2DA, UK.; Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK.",BMC medical informatics and decision making,2019,"BACKGROUND:COPD is a highly heterogeneous disease composed of different phenotypes with different aetiological and prognostic profiles and current classification systems do not fully capture this heterogeneity. In this study we sought to discover, describe and validate COPD subtypes using cluster analysis on data derived from electronic health records. METHODS:We applied two unsupervised learning algorithms (k-means and hierarchical clustering) in 30,961 current and former smokers diagnosed with COPD, using linked national structured electronic health records in England available through the CALIBER resource. We used 15 clinical features, including risk factors and comorbidities and performed dimensionality reduction using multiple correspondence analysis. We compared the association between cluster membership and COPD exacerbations and respiratory and cardiovascular death with 10,736 deaths recorded over 146,466 person-years of follow-up. We also implemented and tested a process to assign unseen patients into clusters using a decision tree classifier. RESULTS:We identified and characterized five COPD patient clusters with distinct patient characteristics with respect to demographics, comorbidities, risk of death and exacerbations. The four subgroups were associated with 1) anxiety/depression; 2) severe airflow obstruction and frailty; 3) cardiovascular disease and diabetes and 4) obesity/atopy. A fifth cluster was associated with low prevalence of most comorbid conditions. CONCLUSIONS:COPD patients can be sub-classified into groups with differing risk factors, comorbidities, and prognosis, based on data included in their primary care records. The identified clusters confirm findings of previous clustering studies and draw attention to anxiety and depression as important drivers of the disease in young, female patients."
 30969971,https://doi.org/10.1371/journal.pone.0213435,Are active children and young people at increased risk of injuries resulting in hospital admission or accident and emergency department attendance? Analysis of linked cohort and electronic hospital records in Wales and Scotland.,"Griffiths LJ, Cortina-Borja M, Tingay K, Bandyopadhyay A, Akbari A, DeStavola BL, Bedford H, Lyons RA, Dezateux C.","Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, United Kingdom.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.; Administrative Data Research Centre Wales, Swansea University Medical School, Swansea, United Kingdom.; National Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, United Kingdom.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, United Kingdom.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, United Kingdom.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.",PloS one,2019,"INTRODUCTION:Children and young people (CYP) are encouraged to increase time spent being physically active, especially in moderate and vigorous intensity pursuits. However, there is limited evidence on the prospective association of activity levels with injuries resulting in use of hospital services. We examined the relationship between objectively-measured physical activity (PA) and subsequent injuries resulting in hospital admissions or accident and emergency department (A&E) attendances, using linked electronic hospital records (EHR) from a nationally representative prospective cohort of CYP in Wales and Scotland. METHODS:We analysed accelerometer-based estimates of moderate to vigorous (MVPA) and vigorous PA (VPA) from 1,585 (777 [46%] boys) seven-year-old Millennium Cohort Study members, living in Wales or Scotland, whose parents consented to linkage of cohort records to EHRs up until their 14th birthday. Negative binomial regression models adjusted by potential individual, household and area-level confounders, were fitted to estimate associations between average daily minutes of MVPA, and VPA (in 10-minute increments), and number of injury-related hospital admissions and/or A&E attendances from age nine to 14 years. RESULTS:CYP spent a median of 59.5 and 18.1 minutes in MVPA and VPA/day respectively, with boys significantly more active than girls; 47.3% of children experienced at least one injury-related admission or A&E attendance during the study period. Rates of injury-related hospital admission and/or A&E attendance were positively associated with MVPA and VPA in boys but not in girls: respective adjusted incidence rate ratios (95% CI) for boys: 1.09 (1.01, 1.17) and 1.16 (1.00, 1.34), and for girls: 0.94 (0.86, 1.03) and 0.85 (0.69, 1.04). CONCLUSION:Boys but not girls who engage in more intense PA at age seven years are at higher risk of injury-related hospital admission or A&E attendance when aged nine to 14 years than their less active peers. This may reflect gender differences in the type and associated risks of activities undertaken. EHRs can make a useful contribution to injury surveillance and prevention if routinely augmented with information on context and setting of the injuries sustained. Injury prevention initiatives should not discourage engagement in PA and outdoor play given their over-riding health and social benefits."
 29743285,https://doi.org/10.1136/bmj.k1717,Risk of stroke and transient ischaemic attack in patients with a diagnosis of resolved atrial fibrillation: retrospective cohort studies.,"Adderley NJ, Nirantharakumar K, Marshall T.","Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.; Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK K.Nirantharan@bham.ac.uk.; Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.",BMJ (Clinical research ed.),2018,"OBJECTIVES:To determine rates of stroke or transient ischaemic attack (TIA) and all cause mortality in patients with a diagnosis of ""resolved"" atrial fibrillation compared to patients with unresolved atrial fibrillation and without atrial fibrillation. DESIGN:Two retrospective cohort studies. SETTING:General practices contributing to The Health Improvement Network, 1 January 2000 to 15 May 2016. PARTICIPANTS:Adults aged 18 years or more with no previous stroke or TIA: 11 159 with resolved atrial fibrillation, 15 059 controls with atrial fibrillation, and 22 266 controls without atrial fibrillation. MAIN OUTCOME MEASURES:Primary outcome was incidence of stroke or TIA. Secondary outcome was all cause mortality. RESULTS:Adjusted incidence rate ratios for stroke or TIA in patients with resolved atrial fibrillation were 0.76 (95% confidence interval 0.67 to 0.85, P<0.001) versus controls with atrial fibrillation and 1.63 (1.46 to 1.83, P<0.001) versus controls without atrial fibrillation. Adjusted incidence rate ratios for mortality in patients with resolved atrial fibrillation were 0.60 (0.56 to 0.65, P<0.001) versus controls with atrial fibrillation and 1.13 (1.06 to 1.21, P<0.001) versus controls without atrial fibrillation. When patients with resolved atrial fibrillation and documented recurrent atrial fibrillation were excluded the adjusted incidence rate ratio for stroke or TIA was 1.45 (1.26 to 1.67, P<0.001) versus controls without atrial fibrillation. CONCLUSION:Patients with resolved atrial fibrillation remain at higher risk of stroke or TIA than patients without atrial fibrillation. The risk is increased even in those in whom recurrent atrial fibrillation is not documented. Guidelines should be updated to advocate continued use of anticoagulants in patients with resolved atrial fibrillation."
 30814958,https://doi.org/10.3389/fpsyt.2019.00036,Risk Assessment Tools and Data-Driven Approaches for Predicting and Preventing Suicidal Behavior.,"Velupillai S, Hadlaczky G, Baca-Garcia E, Gorrell GM, Werbeloff N, Nguyen D, Patel R, Leightley D, Downs J, Hotopf M, Dutta R.","Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.; National Center for Suicide Research and Prevention (NASP), Department of Learning, Informatics, Management and Ethics (LIME), Karolinska Institutet, Stockholm, Sweden.; Department of Psychiatry, IIS-Jimenez Diaz Foundation, Madrid, Spain.; Department of Computer Science, University of Sheffield, Sheffield, United Kingdom.; Division of Psychiatry, University College London, London, United Kingdom.; Alan Turing Institute, London, United Kingdom.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.",Frontiers in Psychiatry,2019,"Risk assessment of suicidal behavior is a time-consuming but notoriously inaccurate activity for mental health services globally. In the last 50 years a large number of tools have been designed for suicide risk assessment, and tested in a wide variety of populations, but studies show that these tools suffer from low positive predictive values. More recently, advances in research fields such as machine learning and natural language processing applied on large datasets have shown promising results for health care, and may enable an important shift in advancing precision medicine. In this conceptual review, we discuss established risk assessment tools and examples of novel data-driven approaches that have been used for identification of suicidal behavior and risk. We provide a perspective on the strengths and weaknesses of these applications to mental health-related data, and suggest research directions to enable improvement in clinical practice."
 29899974,https://doi.org/10.12688/f1000research.13830.2,Knowledge discovery for Deep Phenotyping serious mental illness from Electronic Mental Health records.,"Jackson R, Patel R, Velupillai S, Gkotsis G, Hoyle D, Stewart R.","Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.; Independent Researcher, Manchester, UK.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.",F1000Research,2018,"We demonstrate a scalable approach to discovering new depictions of SMI symptomatology based on real world clinical observation. Such approaches may offer the opportunity to consider broader manifestations of SMI symptomatology than is typically assessed via current diagnostic frameworks, and create the potential for enhancing nomenclatures such as SNOMED CT based on real world depictions."
+30585256,https://doi.org/10.1038/s41416-018-0365-6,"Personal radio use and cancer risks among 48,518 British police officers and staff from the Airwave Health Monitoring Study.","Gao H, Aresu M, Vergnaud AC, McRobie D, Spear J, Heard A, Kongsgård HW, Singh D, Muller DC, Elliott P.","Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Faculty of Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK. p.elliott@imperial.ac.uk.",British journal of cancer,2019,"BACKGROUND:Radiofrequency electromagnetic fields (RF-EMF) from mobile phones have been classified as potentially carcinogenic. No study has investigated use of Terrestrial Trunked Radio (TETRA), a source of RF-EMF with wide occupational use, and cancer risks. METHODS:We investigated association of monthly personal radio use and risk of cancer using Cox proportional hazards regression among 48,518 police officers and staff of the Airwave Health Monitoring Study in Great Britain. RESULTS:During median follow-up of 5.9 years, 716 incident cancer cases were identified. Among users, the median of the average monthly duration of use in the year prior to enrolment was 30.5  min (inter-quartile range 8.1, 68.1). Overall, there was no association between personal radio use and risk of all cancers (hazard ratio [HR] = 0.98, 95% confidence interval [CI]: 0.93, 1.03). For head and neck cancers HR = 0.72 (95% CI: 0.30, 1.70) among personal radio users vs non-users, and among users it was 1.06 (95% CI: 0.91, 1.23) per doubling of minutes of personal radio use. CONCLUSIONS:With the limited follow-up to date, we found no evidence of association of personal radio use with cancer risk. Continued follow-up of the cohort is warranted."
 30524708,https://doi.org/10.1093/ckj/sfy090,The potential for improving cardio-renal outcomes by sodium-glucose co-transporter-2 inhibition in people with chronic kidney disease: a rationale for the EMPA-KIDNEY study.,"Herrington WG, Preiss D, Haynes R, von Eynatten M, Staplin N, Hauske SJ, George JT, Green JB, Landray MJ, Baigent C, Wanner C.","Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Boehringer Ingelheim International, Ingelheim, Germany.; Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Boehringer Ingelheim International, Ingelheim, Germany.; Boehringer Ingelheim International, Ingelheim, Germany.; Duke Clinical Research Institute, Duke University Medical Center, Durham, NC, USA.; Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, UK.; Würzburg University Clinic, Würzburg, Germany.",Clinical Kidney Journal,2018,"Diabetes is a common cause of chronic kidney disease (CKD), but in aggregate, non-diabetic diseases account for a higher proportion of cases of CKD than diabetes in many parts of the world. Inhibition of the renin-angiotensin system reduces the risk of kidney disease progression and treatments that lower blood pressure (BP) or low-density lipoprotein cholesterol reduce cardiovascular (CV) risk in this population. Nevertheless, despite such interventions, considerable risks for kidney and CV complications remain. Recently, large placebo-controlled outcome trials have shown that sodium-glucose co-transporter-2 (SGLT-2) inhibitors reduce the risk of CV disease (including CV death and hospitalization for heart failure) in people with type 2 diabetes who are at high risk of atherosclerotic disease, and these effects were largely independent of improvements in hyperglycaemia, BP and body weight. In the kidney, increased sodium delivery to the macula densa mediated by SGLT-2 inhibition has the potential to reduce intraglomerular pressure, which may explain why SGLT-2 inhibitors reduce albuminuria and appear to slow kidney function decline in people with diabetes. Importantly, in the trials completed to date, these benefits appeared to be maintained at lower levels of kidney function, despite attenuation of glycosuric effects, and did not appear to be dependent on ambient hyperglycaemia. There is therefore a rationale for studying the cardio-renal effects of SGLT-2 inhibition in people at risk of CV disease and hyperfiltration (i.e. those with substantially reduced nephron mass and/or albuminuria), irrespective of whether they have diabetes."
 30082368,https://doi.org/10.1136/bmjopen-2018-024755,Validating injury burden estimates using population birth cohorts and longitudinal cohort studies of injury outcomes: the VIBES-Junior study protocol.,"Gabbe BJ, Dipnall JF, Lynch JW, Rivara FP, Lyons RA, Ameratunga S, Brussoni M, Lecky FE, Bradley C, Simpson PM, Beck B, Demmler JC, Lyons J, Schneeberg A, Harrison JE.","School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; School of Public Health, University of Adelaide, Adelaide, South Australia, Australia.; Departments of Pediatrics and Epidemiology, and the Harborview Injury Prevention and Research Center, University of Washington, Seattle, Washington, USA.; Health Data Research UK, Swansea University, Swansea, UK.; School of Population Health, University of Auckland, Auckland, New Zealand.; Department of Pediatrics, School of Population and Public Health, University of British Columbia, Vancouver, Canada.; School of Health and Related Research, University of Sheffield, Sheffield, UK.; South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia.; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.; British Columbia Injury Research and Prevention Unit, Children's Hospital Research Institute, Vancouver, Canada.; Research Centre for Injury Studies, Flinders University, Adelaide, South Australia, Australia.",BMJ open,2018,"Traumatic injury is a leading contributor to the global disease burden in children and adolescents, but methods used to estimate burden do not account for differences in patterns of injury and recovery between children and adults. A lack of empirical data on postinjury disability in children has limited capacity to derive valid disability weights and describe the long-term individual and societal impacts of injury in the early part of life. The aim of this study is to establish valid estimates of the burden of non-fatal injury in children and adolescents.Five longitudinal studies of paediatric injury survivors <18 years at the time of injury (Australia, Canada, UK and USA) and two whole-of-population linked administrative data paediatric studies (Australia and Wales) will be analysed over a 3-year period commencing 2018. Meta-analysis of deidentified patient-level data (n≈2,600) from five injury-specific longitudinal studies (Victorian State Trauma Registry; Victorian Orthopaedic Trauma Outcomes Registry; UK Burden of Injury; British Columbia Children's Hospital Longitudinal Injury Outcomes; Children's Health After Injury) and >1 million children from two whole-of-population cohorts (South Australian Early Childhood Data Project and Wales Electronic Cohort for Children). Systematic analysis of pooled injury-specific cohort data using a variety of statistical techniques, and parallel analysis of whole-of-population cohorts, will be used to develop estimated disability weights for years lost due to disability, establish appropriate injury classifications and explore factors influencing recovery.The project was approved by the Monash University Human Research Ethics Committee project number 12 311. Results of this study will be submitted for publication in internationally peer-reviewed journals. The findings from this project have the capacity to improve the validity of paediatric injury burden measurements in future local and global burden of disease studies."
 30801036,https://doi.org/10.12688/wellcomeopenres.15007.1,Million Migrants study of healthcare and mortality outcomes in non-EU migrants and refugees to England: Analysis protocol for a linked population-based cohort study of 1.5 million migrants.,"Burns R, Pathak N, Campos-Matos I, Zenner D, Vittal Katikireddi S, Muzyamba MC, Miranda JJ, Gilbert R, Rutter H, Jones L, Williamson E, Hayward AC, Smeeth L, Abubakar I, Hemingway H, Aldridge RW.","Centre for Public Health Data Science, University College London, London, UK.; Centre for Public Health Data Science, University College London, London, UK.; Public Health England, London, UK.; Migration Health Division, International Organization for Migration, Brussels, Belgium.; MRC/CSO Social and Public Health Sciences Unit, Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.; Public Health England, London, UK.; CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.; Institute of Epidemiology and Healthcare, University College London, London, UK.; Faculty of Humanities and Social Sciences, University of Bath, Bath, UK.; UK programme manager, Doctors of the World, London, UK.; Faculty of Epidemiology & Population Health, London School of Hygiene and Tropical Medicine, London, UK.; Institute of Epidemiology and Healthcare, University College London, London, UK.; Department of Non-Communicable Diseases Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.; Institute for Global Health, University College London, London, UK.; Institute of Health Informatics Research, Faculty of Population Health Sciences, University College London, London, UK.; Centre for Public Health Data Science, University College London, London, UK.",Wellcome open research,2019,"Background: In 2017, 15.6% of the people living in England were born abroad, yet we have a limited understanding of their use of health services and subsequent health conditions. This linked population-based cohort study aims to describe the hospital-based healthcare and mortality outcomes of 1.5 million non-European Union (EU) migrants and refugees in England. Methods and analysis: We will link four data sources: first, non-EU migrant tuberculosis pre-entry screening data; second, refugee pre-entry health assessment data; third, national hospital episode statistics; and fourth, Office of National Statistics death records. Using this linked dataset, we will then generate a population-based cohort to examine hospital-based events and mortality outcomes in England between Jan 1, 2006, and Dec 31, 2017. We will compare outcomes across three groups in our analyses: 1) non-EU international migrants, 2) refugees, and 3) general population of England. Ethics and dissemination: We will obtain approval to use unconsented patient identifiable data from the Secretary of State for Health through the Confidentiality Advisory Group and the National Health Service Research Ethics Committee. After data linkage, we will destroy identifying data and undertake all analyses using the pseudonymised dataset. The results will provide policy makers and civil society with detailed information about the health needs of non-EU international migrants and refugees in England."
@@ -43,23 +53,24 @@ id,doi,title,authorString,authorAffiliations,journalTitle,pubYear,abstract
 30537243,https://doi.org/10.1002/ejhf.1370,"Can advanced analytics fix modern medicine's problem of uncertainty, imprecision, and inaccuracy?","Ahmad T, Freeman JV, Asselbergs FW.","Section of Cardiovascular Medicine, Yale University School of Medicine, New Haven, CT, USA.; Section of Cardiovascular Medicine, Yale University School of Medicine, New Haven, CT, USA.; Health Data Research UK and Institute of Health Informatics, University College London, London, UK.",European journal of heart failure,2019,
 30940752,https://doi.org/10.1136/bmjopen-2018-023232,Using natural language processing to extract structured epilepsy data from unstructured clinic letters: development and validation of the ExECT (extraction of epilepsy clinical text) system.,"Fonferko-Shadrach B, Lacey AS, Roberts A, Akbari A, Thompson S, Ford DV, Lyons RA, Rees MI, Pickrell WO.","Neurology and Molecular Neuroscience Group, Institute of Life Science, Swansea University Medical School, Swansea University, Swansea, UK.; Neurology and Molecular Neuroscience Group, Institute of Life Science, Swansea University Medical School, Swansea University, Swansea, UK.; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.; Health Data Research UK, Data Science Building, Swansea University Medical School, Swansea University, Swansea, UK.; Health Data Research UK, Data Science Building, Swansea University Medical School, Swansea University, Swansea, UK.; Health Data Research UK, Data Science Building, Swansea University Medical School, Swansea University, Swansea, UK.; Health Data Research UK, Data Science Building, Swansea University Medical School, Swansea University, Swansea, UK.; Neurology and Molecular Neuroscience Group, Institute of Life Science, Swansea University Medical School, Swansea University, Swansea, UK.; Neurology and Molecular Neuroscience Group, Institute of Life Science, Swansea University Medical School, Swansea University, Swansea, UK.",BMJ open,2019,"OBJECTIVE:Routinely collected healthcare data are a powerful research resource but often lack detailed disease-specific information that is collected in clinical free text, for example, clinic letters. We aim to use natural language processing techniques to extract detailed clinical information from epilepsy clinic letters to enrich routinely collected data. DESIGN:We used the general architecture for text engineering (GATE) framework to build an information extraction system, ExECT (extraction of epilepsy clinical text), combining rule-based and statistical techniques. We extracted nine categories of epilepsy information in addition to clinic date and date of birth across 200 clinic letters. We compared the results of our algorithm with a manual review of the letters by an epilepsy clinician. SETTING:De-identified and pseudonymised epilepsy clinic letters from a Health Board serving half a million residents in Wales, UK. RESULTS:We identified 1925 items of information with overall precision, recall and F1 score of 91.4%, 81.4% and 86.1%, respectively. Precision and recall for epilepsy-specific categories were: epilepsy diagnosis (88.1%, 89.0%), epilepsy type (89.8%, 79.8%), focal seizures (96.2%, 69.7%), generalised seizures (88.8%, 52.3%), seizure frequency (86.3%-53.6%), medication (96.1%, 94.0%), CT (55.6%, 58.8%), MRI (82.4%, 68.8%) and electroencephalogram (81.5%, 75.3%). CONCLUSIONS:We have built an automated clinical text extraction system that can accurately extract epilepsy information from free text in clinic letters. This can enhance routinely collected data for research in the UK. The information extracted with ExECT such as epilepsy type, seizure frequency and neurological investigations are often missing from routinely collected data. We propose that our algorithm can bridge this data gap enabling further epilepsy research opportunities. While many of the rules in our pipeline were tailored to extract epilepsy specific information, our methods can be applied to other diseases and also can be used in clinical practice to record patient information in a structured manner."
 31109684,https://doi.org/10.1016/j.injury.2019.05.004,Agreement between medical record and administrative coding of common comorbidities in orthopaedic trauma patients.,"Daly S, Nguyen TQ, Gabbe BJ, Braaf S, Simpson P, Ekegren CL.","School of Medicine, Monash University, Melbourne, VIC, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia; Health Data Research, UK.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia. Electronic address: christina.ekegren@monash.edu.",Injury,2019,"OBJECTIVE:To i) quantify the agreement between comorbidities documented within medical records and an orthopaedic trauma dataset; and ii) compare agreement between these sources before and after the introduction of new comorbidity coding rules in Australian hospitals. STUDY DESIGN AND SETTING:A random sample of adult (≥ 16 years) orthopaedic trauma patients (n = 400) were extracted from the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR). Diagnoses of obesity, arthritis, diabetes and cardiac conditions documented within patients' medical records were compared to ICD-10-AM comorbidity codes (provided by hospitals) for the same admission. Agreement was calculated (Cohen's kappa) before and after the introduction of new coding rules. RESULTS:All comorbidities had the same or higher prevalence in medical record data compared to coded data. Kappa values ranged from <0.001 (poor agreement) for coronary artery disease to 0.94 (excellent agreement) for type 2 diabetes. There was improvement in agreement between sources for most conditions following the introduction of new coding rules. CONCLUSION:There has been improvement in the coding of certain comorbidities since the introduction of new coding rules, suggesting that, since 2015, administrative data has improved capacity to capture patients' comorbidity profiles. Consideration must be taken when using the ICD-10-AM data due to its limitations."
-30729733,https://doi.org/10.1111/ijpo.12512,Predictors of objectively measured physical activity in 12-month-old infants: A study of linked birth cohort data with electronic health records.,"Raza H, Zhou SM, Todd C, Christian D, Marchant E, Morgan K, Khanom A, Hill R, Lyons RA, Brophy S.","The School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Department of Sport and Physical Activity, Edge Hill University, Ormskirk, UK.; Health Data Research UK, Swansea University, Swansea, UK.; DECIPHer, School of Social Sciences, Cardiff University, Cardiff, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Abertawe Bro Morgannwg University Health Board (ABM UHB), Port Talbot, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Health Data Research UK, Swansea University, Swansea, UK.",Pediatric obesity,2019,"BACKGROUND:Physical activity (PA) levels are associated with long-term health, and levels of PA when young are predictive of adult activity levels. OBJECTIVES:This study examines factors associated with PA levels in 12-month infants. METHOD:One hundred forty-one mother-infant pairs were recruited via a longitudinal birth cohort study (April 2010 to March 2013). The PA level was collected using accelerometers and linked to postnatal notes and electronic medical records via the Secure Anonymised Information Linkage databank. Univariable and multivariable linear regressions were used to examine the factors associated with PA levels. RESULTS:Using univariable analysis, higher PA was associated with the following (P value less than 0.05): being male, larger infant size, healthy maternal blood pressure levels, full-term gestation period, higher consumption of vegetables (infant), lower consumption of juice (infant), low consumption of adult crisps (infant), longer breastfeeding duration, and more movement during sleep (infant) but fewer night wakings. Combined into a multivariable regression model (R2  = 0.654), all factors remained significant, showing lower PA levels were associated with female gender, smaller infant, preterm birth, higher maternal blood pressure, low vegetable consumption, high crisp consumption, and less night movement. CONCLUSION:The PA levels of infants were strongly associated with both gestational and postnatal environmental factors. Healthy behaviours appear to cluster, and a healthy diet was associated with a more active infant. Boys were substantially more active than girls, even at age 12 months. These findings can help inform interventions to promote healthier lives for infants and to understand the determinants of their PA levels."
 30444743,https://doi.org/10.1097/ccm.0000000000003424,"Risk Factors for 1-Year Mortality and Hospital Utilization Patterns in Critical Care Survivors: A Retrospective, Observational, Population-Based Data Linkage Study.","Szakmany T, Walters AM, Pugh R, Battle C, Berridge DM, Lyons RA.","Division of Population Medicine, Department of Anaesthesia, Intensive Care and Pain Medicine, Cardiff University, Heath Park Campus, Cardiff, United Kingdom.; Health Data Research UK, Swansea University Medical School, Data Science Building, Swansea, United Kingdom.; Department of Anaesthetic, Glan Clywdd Hospital, Betsi Cadwaladar University Health Board, Bodelwyddan, Rhyl, United Kingdom.; Morriston Hospital, Abertawe Bro Morgannwg University Health Board, Heol Maes Eglwys, Swansea, United Kingdom.; Health Data Research UK, Swansea University Medical School, Data Science Building, Swansea, United Kingdom.; Health Data Research UK, Swansea University Medical School, Data Science Building, Swansea, United Kingdom.",Critical care medicine,2019,"OBJECTIVES:Clear understanding of the long-term consequences of critical care survivorship is essential. We investigated the care process and individual factors associated with long-term mortality among ICU survivors and explored hospital use in this group. DESIGN:Population-based data linkage study using the Secure Anonymised Information Linkage databank. SETTING:All ICUs between 2006 and 2013 in Wales, United Kingdom. PATIENTS:We identified 40,631 patients discharged alive from Welsh adult ICUs. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:Primary outcome was 365-day survival. The secondary outcomes were 30- and 90-day survival and hospital utilization in the 365 days following ICU discharge. Kaplan-Meier curves were plotted to compare survival rates. Cox proportional hazards regression models were used to determine risk factors of mortality. Seven-thousand eight-hundred eighty-three patients (19.4%) died during the 1-year follow-up period. In the multivariable Cox regression analysis, advanced age and comorbidities were significant determinants of long-term mortality. Expedited discharge due to ICU bed shortage was associated with higher risk. The rate of hospitalization in the year prior to the critical care admission was 28 hospitalized days/1,000 d; post critical care was 88 hospitalized days/1,000 d for those who were still alive; and 57 hospitalized days/1,000 d and 412 hospitalized days/1,000 d for those who died by the end of the study, respectively. CONCLUSIONS:One in five ICU survivors die within 1 year, with advanced age and comorbidity being significant predictors of outcome, leading to high resource use. Care process factors indicating high system stress were associated with increased risk. More detailed understanding is needed on the effects of the potentially modifiable factors to optimize service delivery and improve long-term outcomes of the critically ill."
 31053412,https://doi.org/10.1016/j.burns.2019.04.006,Severe burns in Australian and New Zealand adults: Epidemiology and burn centre care.,"Toppi J, Cleland H, Gabbe B.","Monash University, Department of Epidemiology and Preventive Medicine, Melbourne, Victoria, Australia. Electronic address: jttoppi1@gmail.com.; Monash University, Department of Epidemiology and Preventive Medicine, Melbourne, Victoria, Australia; The Victorian Adult Burns Unit, The Alfred Hospital, Melbourne, Victoria, Australia; Department of Surgery, Monash University Central Clinical School, Melbourne, Victoria, Australia.; Monash University, Department of Epidemiology and Preventive Medicine, Melbourne, Victoria, Australia; Health Data Research UK, Swansea UniversityMedical School, Swansea University, Swansea, United Kingdom.",Burns : journal of the International Society for Burn Injuries,2019,"INTRODUCTION:Studies describing the epidemiology of severe burns (>20% total body surface area) in adults are limited despite the extensive associated morbidity and mortality. This study aimed to describe the epidemiology of severe burn injuries admitted to burn centres in Australia and New Zealand. MATERIALS AND METHODS:Data from the Burns Registry of Australia and New Zealand (BRANZ) were used in this study. Patients were eligible for inclusion if they were admitted between August 2009 and June 2013, were adults (18-years or older), and had burns of 20% total body surface area (TBSA) or greater. Demographics, burn characteristics and in-hospital mortality risk factors were investigated using multivariable Cox proportional hazards analysis. RESULTS:There were 496 BRANZ registered patients who met the inclusion criteria. Over half of the patients were aged 18-40 years and most were male. The median (IQR) TBSA was 31 (25-47). Most (75%) patients had burns involving <50% TBSA, 58% sustained their burn injury at home, and 86% had sustained flame burns. Leisure activities, working for income and preparing food together accounted for over 48% of the activities undertaken at the time of injury. The in-hospital mortality rate was 17% and the median (IQR) length of stay was 24 (12-44) days. Seventy-two percent were admitted to an intensive care unit (ICU) and 40% of patients had an associated inhalation injury. Alcohol and/or drug involvement was suspected in 25% of cases. CONCLUSION:This study describes the demographics, burn injury characteristics and in-hospital outcomes of severe burn injuries in adults whilst also identifying key predictors of inpatient mortality. Key findings included the over-representation of young males, intentional self-harm injuries and flame as a cause of burns and highlights high risk groups to help aid in the development of targeted prevention strategies."
 30887727,https://doi.org/10.1002/ppul.24314,Physical activity among children with asthma: Cross-sectional analysis in the UK millennium cohort.,"Pike KC, Griffiths LJ, Dezateux C, Pearce A.","Infection, Immunity and Inflammation Academic Programme, Great Ormond Street Institute of Child Health, University College London, London, UK.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Centre for Primary Care and Public Health, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.",Pediatric pulmonology,2019,"BACKGROUND:Although beneficial for health and well-being, most children do not achieve recommended levels of physical activity. Evidence for children with asthma is mixed, with symptom severity rarely considered. This paper aimed to address this gap. METHODS:We analyzed cross-sectional associations between physical activity and parent-reported asthma symptoms and severity for 6497 UK Millennium Cohort Study 7-year-old participants (3321, [49%] girls). Primary outcomes were daily moderate-to-vigorous physical activity (MVPA, minutes) and proportion of children achieving recommended minimum daily levels of 60 minutes of MVPA. Daily steps, sedentary time, and total activity counts per minute (cpm) were recorded, as were parent-reported asthma symptoms, medications, and recent hospital admissions. Associations were investigated using quantile (continuous outcomes) and Poisson (binary outcomes) regression, adjusting for demographic, socioeconomic, health, and environmental factors. RESULTS:Neither asthma status nor severity was associated with MVPA; children recently hospitalized for asthma were less likely to achieve recommended daily MVPA (risk ratio [95% confidence interval [CI]]: 0.67 [0.44, 1.03]). Recent wheeze, current asthma, and severe asthma symptoms were associated with fewer sedentary hours (difference in medians [95% CI]: -0.18 [-0.27, -0.08]; -0.14 [-0.24, -0.05]; -0.15, [-0.28, -0.02], respectively) and hospital admission with lower total activity (-48 cpm [-68, -28]). CONCLUSION:Children with asthma are as physically active as their asthma-free counterparts, while those recently hospitalized for asthma are less active. Qualitative studies are needed to understand the perceptions of children and families about physical activity following hospital admission and to inform support and advice needed to maintain active lifestyles for children with asthma."
-30659777,https://doi.org/10.1111/ijpo.12505,Are children with clinical obesity at increased risk of inpatient hospital admissions? An analysis using linked electronic health records in the UK millennium cohort study.,"Griffiths LJ, Cortina-Borja M, Bandyopadhyay A, Tingay K, De Stavola BL, Bedford H, Akbari A, Firman N, Lyons RA, Dezateux C.","Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; National Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, UK.; Administrative Data Research Centre Wales, Swansea University Medical School, Swansea, UK.; Clinical Epidemiology, Nutrition and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.; Health Data Research UK, Wales and Northern Ireland, Swansea University Medical School, Swansea, UK.; Life Course Epidemiology and Biostatistics, UCL Great Ormond Street Institute of Child Health, London, UK.",Pediatric obesity,2019,"BACKGROUND:Few studies have examined health service utilization of children with overweight or obesity by using linked electronic health records (EHRs). OBJECTIVE/METHODS:We analysed EHRs from 3269 children (1678 boys; 51.3% [weighted]) participating in the Millennium Cohort Study, living in Wales or Scotland at age seven whose parents consented to record linkage. We used height and weight measurements at age five to categorize children as obese (>98th centile) or overweight (>91st centile) (UK1990 clinical reference standards) and linked to hospital admissions, up to age 14 years, in the Patient Episode Database for Wales and Scottish Morbidity Records. Negative binomial regression models compared rates of inpatient admissions by weight status at age five. RESULTS:At age five, 11.5% and 6.7% of children were overweight or obese, respectively; 1221 (38%) children were subsequently admitted to hospital at least once. Admissions were not increased among children with overweight or obesity (adjusted rate ratio [RR], 95% confidence interval [CI]: 0.87, 0.68-1.10 and 1.16, 0.87-1.54, respectively). CONCLUSIONS:In this nationally representative cohort of children in Wales and Scotland, those with overweight or obesity at entry to primary school did not have increased rates of hospital admissions in later childhood and early adolescence."
 31113941,https://doi.org/10.1038/s41467-019-10417-4,Author Correction: Towards a data-integrated cell.,"Malod-Dognin N, Petschnigg J, Windels SFL, Povh J, Hemingway H, Ketteler R, Pržulj N.","Department of Computer Science, University College London, London, WC1E 6BT, UK.; Department of Computer Science, University College London, London, WC1E 6BT, UK.; Department of Computer Science, University College London, London, WC1E 6BT, UK.; Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana, 1000, Slovenia.; Health Data Research UK London, University College London, London, WC1E 6BT, UK.; MRC Laboratory for Molecular Cell Biology, University College London, London, WC1E 6BT, UK.; Department of Computer Science, University College London, London, WC1E 6BT, UK. natasa@cs.ucl.ac.uk.",Nature communications,2019,"The original version of this Article contained an error in the spelling of the author Harry Hemingway, which was incorrectly given as Harry Hemmingway. This has been corrected in both the PDF and HTML versions of the Article."
 31040096,https://doi.org/10.1016/s2352-4642(19)30114-2,"Antimicrobial-impregnated central venous catheters for prevention of neonatal bloodstream infection (PREVAIL): an open-label, parallel-group, pragmatic, randomised controlled trial.","Gilbert R, Brown M, Rainford N, Donohue C, Fraser C, Sinha A, Dorling J, Gray J, McGuire W, Gamble C, Oddie SJ, PREVAIL trial team.","UCL Great Ormond Street Institute of Child Health, London, UK; Health Data Research UK, London, UK. Electronic address: r.gilbert@ucl.ac.uk.; Clinical Trials Research Centre, Department of Biostatistics, University of Liverpool, Liverpool, UK.; Clinical Trials Research Centre, Department of Biostatistics, University of Liverpool, Liverpool, UK.; Clinical Trials Research Centre, Department of Biostatistics, University of Liverpool, Liverpool, UK.; UCL Great Ormond Street Institute of Child Health, London, UK.; Barts Health NHS Trust, London, UK; Blizard Institute, Queen Mary University of London, London, UK.; Division of Neonatal-Perinatal Medicine, Dalhousie University IWK Health Centre, Halifax, NS, Canada.; Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK.; Centre for Reviews and Dissemination, University of York, York, UK.; Clinical Trials Research Centre, Department of Biostatistics, University of Liverpool, Liverpool, UK.; Centre for Reviews and Dissemination, University of York, York, UK; Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK.",The Lancet. Child & adolescent health,2019,"BACKGROUND:Bloodstream infection is associated with high mortality and serious morbidity in preterm babies. Evidence from clinical trials shows that antimicrobial-impregnated central venous catheters (CVCs) reduce catheter-related bloodstream infection in adults and children receiving intensive care, but there is a paucity of similar evidence for babies receiving neonatal intensive care. METHODS:This open-label, parallel-group, pragmatic, randomised controlled trial was done in 18 neonatal intensive care units in England. Newborn babies who needed a peripherally inserted CVC (PICC) were allocated randomly (1:1) to receive either a PICC impregnated with miconazole and rifampicin or a standard (non-antimicrobial-impregnated) PICC. Random allocation was done with a web-based program, which was centrally controlled to ensure allocation concealment. Randomisation sequences were computer-generated in random blocks of two and four, and stratified by site. Masking of clinicians to PICC allocation was impractical because rifampicin caused brown staining of the antimicrobial-impregnated PICC. However, participant inclusion in analyses and occurrence of outcome events were determined following an analysis plan that was specified before individuals saw the unblinded data. The primary outcome was the time from random allocation to first microbiologically confirmed bloodstream or cerebrospinal fluid (CSF) infection between 24 h after randomisation and 48 h after PICC removal or death. We analysed outcome data according to the intention-to-treat principle. We excluded babies for whom a PICC was not inserted from safety analyses, as these analyses were done with groups defined by the PICC used. This trial is registered with ISRCTN, number 81931394. FINDINGS:Between Aug 12, 2015, and Jan 11, 2017, we randomly assigned 861 babies (754 [88%] born before 32 weeks of gestation) to receive an antimicrobial-impregnated PICC (430 babies) or standard PICC (431 babies). The median time to PICC removal was 8·20 days (IQR 4·77-12·13) in the antimicrobial-impregnated PICC group versus 7·86 days (5·00-12·53) days in the standard PICC group (hazard ratio [HR] 1·03, 95% CI 0·89-1·18, p=0·73), with 46 (11%) of 430 babies versus 44 (10%) of 431 babies having a microbiologically confirmed bloodstream or CSF infection. The time from random allocation to first bloodstream or CSF infection was similar between the two groups (HR 1·11, 95% CI 0·73-1·67, p=0·63). Secondary outcomes relating to infection, rifampicin resistance in positive blood or CSF cultures, mortality, clinical outcomes at neonatal unit discharge, and time to PICC removal were similar between the two groups, although rifampicin resistance in positive cultures of PICC tips was higher in the antimicrobial-impregnated PICC group (relative risk 3·51, 95% CI 1·16-10·57, p=0·018). 60 adverse events were reported from 49 (13%) patients in the antimicrobial-impregnated PICC group and 50 events from 45 (10%) babies in the standard PICC group. INTERPRETATION:We found no evidence of benefit or harm associated with miconazole and rifampicin-impregnated PICCs compared with standard PICCs for newborn babies. Future research should focus on other types of antimicrobial impregnation of PICCs and alternative approaches for preventing infection. FUNDING:UK National Institute for Health Research Health Technology Assessment programme."
 30102210,https://doi.org/10.1016/s1470-2045(18)30425-x,A roadmap for restoring trust in Big Data.,"Lawler M, Morris AD, Sullivan R, Birney E, Middleton A, Makaroff L, Knoppers BM, Horgan D, Eggermont A.","Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast BT9 7BL, UK; European Alliance for Personalised Medicine, Brussels, Belgium; Global Alliance for Genomics and Health, Boston, MA, USA; Health Data Research UK, London, UK. Electronic address: mark.lawler@qub.ac.uk.; Health Data Research UK, London, UK.; Institute for Cancer Policy, Kings College London, London, UK.; Global Alliance for Genomics and Health, Boston, MA, USA; European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK.; Global Alliance for Genomics and Health, Boston, MA, USA; Welcome Genome Campus, Society and Ethics Research, Cambridge, UK.; European Cancer Patient Coalition, Brussels, Belgium; University of Leuven, Leuven, Belgium.; Global Alliance for Genomics and Health, Boston, MA, USA; Centre for Genomics and Policy, McGill University, Montreal, QC, Canada.; European Alliance for Personalised Medicine, Brussels, Belgium.; European Alliance for Personalised Medicine, Brussels, Belgium; Gustave Roussy Cancer Campus Grand Paris, Villejuif, France.",The Lancet. Oncology,2018,
 30928767,https://doi.org/10.1016/j.evalprogplan.2019.03.002,Understanding the factors that influence health promotion evaluation: The development and validation of the evaluation practice analysis survey.,"Schwarzman J, Bauman A, Gabbe BJ, Rissel C, Shilton T, Smith BJ.","School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC, 3004, Australia. Electronic address: joanna.schwarzman@monash.edu.; Prevention Research Collaboration, School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia.; School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC, 3004, Australia; Health Data Research UK, Swansea UniversityMedical School, Swansea University, Singleton Park, Swansea, SA2 8PP, Wales, UK.; Prevention Research Collaboration, School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia.; National Heart Foundation of Australia, 334 Rokeby Road, Subiaco, WA 6008, Australia.; School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC, 3004, Australia; Prevention Research Collaboration, School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia.",Evaluation and program planning,2019,"The demand for improved quality of health promotion evaluation and greater capacity to undertake evaluation is growing, yet evidence of the challenges and facilitators to evaluation practice within the health promotion field is lacking. A limited number of evaluation capacity measurement instruments have been validated in government or non-government organisations (NGO), however there is no instrument designed for health promotion organisations. This study aimed to develop and validate an Evaluation Practice Analysis Survey (EPAS) to examine evaluation practices in health promotion organisations. Qualitative interviews, existing frameworks and instruments informed the survey development. Health promotion practitioners from government agencies and NGOs completed the survey (n = 169). Principal components analysis was used to determine scale structure and Cronbach's α used to estimate internal reliability. Logistic regression was conducted to assess predictive validity of selected EPAS scale. The final survey instrument included 25 scales (125 items). The EPAS demonstrated good internal reliability (α > 0.7) for 23 scales. Dedicated resources and time for evaluation, leadership, organisational culture and internal support for evaluation showed promising predictive validity. The EPAS can be used to describe elements of evaluation capacity at the individual, organisational and system levels and to guide initiatives to improve evaluation practice in health promotion organisations."
 30778056,https://doi.org/10.1038/s41467-019-08797-8,Towards a data-integrated cell.,"Malod-Dognin N, Petschnigg J, Windels SFL, Povh J, Hemingway H, Ketteler R, Pržulj N.","Department of Computer Science, University College London, London, WC1E 6BT, UK.; Department of Computer Science, University College London, London, WC1E 6BT, UK.; Department of Computer Science, University College London, London, WC1E 6BT, UK.; Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana, 1000, Slovenia.; Health Data Research UK London, University College London, London, WC1E 6BT, UK.; MRC Laboratory for Molecular Cell Biology, University College London, London, WC1E 6BT, UK.; Department of Computer Science, University College London, London, WC1E 6BT, UK. natasa@cs.ucl.ac.uk.",Nature communications,2019,"We are increasingly accumulating molecular data about a cell. The challenge is how to integrate them within a unified conceptual and computational framework enabling new discoveries. Hence, we propose a novel, data-driven concept of an integrated cell, iCell. Also, we introduce a computational prototype of an iCell, which integrates three omics, tissue-specific molecular interaction network types. We construct iCells of four cancers and the corresponding tissue controls and identify the most rewired genes in cancer. Many of them are of unknown function and cannot be identified as different in cancer in any specific molecular network. We biologically validate that they have a role in cancer by knockdown experiments followed by cell viability assays. We find additional support through Kaplan-Meier survival curves of thousands of patients. Finally, we extend this analysis to uncover pan-cancer genes. Our methodology is universal and enables integrative comparisons of diverse omics data over cells and tissues."
+31204027,https://doi.org/10.1016/j.injury.2019.06.012,"Comparing the outcomes of isolated, serious traumatic brain injury in older adults managed at major trauma centres and neurosurgical services: A registry-based cohort study.","Dunn MS, Beck B, Simpson PM, Cameron PA, Kennedy M, Maiden M, Judson R, Gabbe BJ.","Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia. Electronic address: matthew.dunn@monash.edu.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; Emergency and Trauma Centre, The Alfred Hospital, Melbourne, Victoria, Australia.; Adult Retrieval Victoria, Ambulance Victoria, Melbourne, Victoria, Australia.; Department of Intensive Care, Geelong University Hospital, Geelong, Australia; Department of Intensive Care, Royal Adelaide Hospital, Adelaide, Australia.; Department of General Surgery, The Royal Melbourne Hospital, Melbourne, Victoria, Australia; Department of Surgery, The University of Melbourne, Melbourne, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; Health Data Research UK, Swansea University Medical School, Swansea University, Swansea, United Kingdom.",Injury,2019,"BACKGROUND:The incidence of older adult traumatic brain injury (TBI) is increasing in both high and middle to low-income countries. It is unknown whether older adults with isolated, serious TBI can be safely managed outside of major trauma centres. This registry based cohort study aimed to compare mortality and functional outcomes of older adults with isolated, serious TBI who were managed at specialised Major Trauma Services (MTS) and Metropolitan Neurosurgical Services (MNS). METHOD:Older adults (65 years and over) who sustained an isolated, serious TBI following a low fall (from standing or ≤ 1 m) were extracted from the Victorian State Trauma Registry from 2007 to 2016. Multivariable models were fitted to assess the association between hospital designation (MTS vs. MNS) and the two outcomes of interest: in-hospital mortality and functional outcome, adjusting for potential confounders. Functional outcomes were measured using the Glasgow Outcome Scale Extended at six months post-injury. RESULTS:From 2007-2016, there were 1904 older adults who sustained an isolated, serious TBI from a low fall who received definitive care at an MTS (n = 1124) or an MNS (n = 780). After adjusting for confounders, there was no mortality benefit for patients managed at an MTS over an MNS (OR = 0.84; 95% CI: 0.65, 1.08; P = 0.17) or improvement in functional outcome six months post-injury (OR = 1.13; 95% CI: 0.94, 1.36; P = 0.21). CONCLUSION:For older adults with isolated, serious TBI following a low fall, there was no difference in mortality or functional outcome based on definitive management at an MTS or an MNS. This confirms that MNS without the added designation of a major trauma centre are a suitable destination for the management of isolated, serious TBI in older adults."
 30981377,https://doi.org/10.1016/j.aap.2019.03.007,How much space do drivers provide when passing cyclists? Understanding the impact of motor vehicle and infrastructure characteristics on passing distance.,"Beck B, Chong D, Olivier J, Perkins M, Tsay A, Rushford A, Li L, Cameron P, Fry R, Johnson M.","Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia. Electronic address: ben.beck@monash.edu.; Faculty of Science, The University of Melbourne, Victoria, Australia.; School of Mathematics and Statistics, University of New South Wales, New South Wales, Australia; School of Aviation, Transport and Road Safety (TARS) Research Centre, University of New South Wales, Sydney, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia.; Faculty of Information Technology, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Emergency and Trauma Centre, The Alfred, Melbourne, Victoria, Australia; National Trauma Research Institute, Victoria, Australia.; Health Data Research UK, Swansea UniversityMedical School,Swansea University, UK.; Institute of Transport Studies, Faculty of Engineering, Monash University, Victoria Australia; Amy Gillett Foundation, Victoria, Australia.",Accident; analysis and prevention,2019,"BACKGROUND:Understanding factors that influence the distance that drivers provide when passing cyclists is critical to reducing subjective risk and improving cycling participation. This study aimed to quantify passing distance and assess the impact of motor vehicle and road infrastructure characteristics on passing distance. METHODS:An on-road observational study was conducted in Victoria, Australia. Participants had a custom device installed on their bicycle and rode as per their usual cycling for one to two weeks. A hierarchical linear model was used to investigate the relationship between motor vehicle and infrastructure characteristics (location, presence of on-road marked bicycle lane and the presence of parked cars on the kerbside) and passing distance (defined as the lateral distance between the end of the bicycle handlebars and the passing motor vehicle). RESULTS:Sixty cyclists recorded 18,527 passing events over 422 trips. The median passing distance was 173 cm (Q1: 137 cm, Q3: 224 cm) and 1085 (5.9%) passing events were less than 100 cm. Relative to sedans, 4WDs had a reduced mean passing distance of 15 cm (Q1: 12 cm, Q3: 17 cm) and buses had a reduced mean passing distance of 28 cm (Q1: 16 cm, Q3: 40 cm). Relative to passing events that occurred on roads without a marked bicycle lane and without parked cars, passing events on roads with a bike lane with no parked cars had a reduced mean passing distance of 27 cm (Q1: 25 cm, Q3: 29 cm), and passing events on roads with a bike lane and parked cars had a mean lower passing distance of 40 cm (Q1: 37 cm, Q3: 43 cm). CONCLUSIONS:One in every 17 passing events was a close (<100 cm) passing event. We identified that on-road bicycle lanes and parked cars reduced passing distance. These data can be used to inform the selection and design of cycling-related infrastructure and road use with the aim of improving safety for cyclists."
 30014898,https://doi.org/10.1016/j.envres.2018.07.015,Estimation of TETRA radio use in the Airwave Health Monitoring Study of the British police forces.,"Vergnaud AC, Aresu M, Kongsgård HW, McRobie D, Singh D, Spear J, Heard A, Gao H, Carpenter JR, Elliott P.","Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Faculty of Medicine, Norwegian University of Science and Technology (NTNU), Norway.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.; Medical Statistics Unit, London School of Hygiene and Tropical Medicine London, WC1E 7HT, United Kingdom.; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom; Imperial College London NIHR Biomedical Research Centre, London, United Kingdom; Health Data Research UK-London, London, United Kingdom. Electronic address: p.elliott@imperial.ac.uk.",Environmental research,2018,"BACKGROUND:The Airwave Health Monitoring Study aims to investigate the possible long-term health effects of Terrestrial Trunked Radio (TETRA) use among the police forces in Great Britain. Here, we investigate whether objective data from the network operator could be used to correct for misreporting in self-reported data and expand the radio usage availability in our cohort. METHODS:We estimated average monthly usage of personal radio in the 12 months prior to enrolment from a missing value imputation model and evaluated its performance against objective and self-reported data. Factors associated with TETRA radio usage variables were investigated using Chi-square tests and analysis of variance. RESULTS:The imputed data were better correlated with objective than self-reported usage (Spearman correlation coefficient = 0.72 vs. 0. 52 and kappa 0.56 [95% confidence interval 0.55, 0.56] vs. 0.46 [0.45, 0.47]), although the imputation model tended to under-estimate use for higher users. Participants with higher personal radio usage were more likely to be younger, men vs. women and officer vs. staff. The median average monthly usage level for the entire cohort was estimated to be 29.3 min (95% CI: [7.2, 66.6]). CONCLUSION:The availability of objective personal radio records for a large proportion of users allowed us to develop a robust imputation model and hence obtain personal radio usage estimates for ~50,000 participants. This substantially reduced exposure misclassification compared to using self-reported data and will allow us to carry out analyses of TETRA usage for the entire cohort in future work."
-30949070,https://doi.org/10.3389/fpsyt.2019.00109,Real World Implementation of a Transdiagnostic Risk Calculator for the Automatic Detection of Individuals at Risk of Psychosis in Clinical Routine: Study Protocol.,"Fusar-Poli P, Oliver D, Spada G, Patel R, Stewart R, Dobson R, McGuire P.","Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.",Frontiers in psychiatry,2019,"Background: Primary indicated prevention in individuals at-risk for psychosis has the potential to improve the outcomes of this disorder. The ability to detect the majority of at-risk individuals is the main barrier toward extending benefits for the lives of many adolescents and young adults. Current detection strategies are highly inefficient. Only 5% (standalone specialized early detection services) to 12% (youth mental health services) of individuals who will develop a first psychotic disorder can be detected at the time of their at-risk stage. To overcome these challenges a pragmatic, clinically-based, individualized, transdiagnostic risk calculator has been developed to detect individuals at-risk of psychosis in secondary mental health care at scale. This calculator has been externally validated and has demonstrated good prognostic performance. However, it is not known whether it can be used in the real world clinical routine. For example, clinicians may not be willing to adhere to the recommendations made by the transdiagnostic risk calculator. Implementation studies are needed to address pragmatic challenges relating to the real world use of the transdiagnostic risk calculator. The aim of the current study is to provide in-vitro and in-vivo feasibility data to support the implementation of the transdiagnostic risk calculator in clinical routine. Method: This is a study which comprises of two subsequent phases: an in-vitro phase of 1 month and an in-vivo phase of 11 months. The in-vitro phase aims at developing and integrating the transdiagnostic risk calculator in the local electronic health register (primary outcome). The in-vivo phase aims at addressing the clinicians' adherence to the recommendations made by the transdiagnostic risk calculator (primary outcome) and other secondary feasibility parameters that are necessary to estimate the resources needed for its implementation. Discussion: This is the first implementation study for risk prediction models in individuals at-risk for psychosis. Ultimately, successful implementation is the true measure of a prediction model's utility. Therefore, the overall translational deliverable of the current study would be to extend the benefits of primary indicated prevention and improve outcomes of first episode psychosis. This may produce significant social benefits for many adolescents and young adults and their families."
 29944675,https://doi.org/10.1371/journal.pone.0199026,"The diagnosis, burden and prognosis of dementia: A record-linkage cohort study in England.","Pujades-Rodriguez M, Assi V, Gonzalez-Izquierdo A, Wilkinson T, Schnier C, Sudlow C, Hemingway H, Whiteley WN.","Leeds Institute of Health Sciences, University of Leeds, Leeds, United Kingdom.; Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom.; Institute of Health Informatics, University College London, London, United Kingdom.; Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom.; Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom.; Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom.; Institute of Health Informatics, University College London, London, United Kingdom.; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.",PloS one,2018,"OBJECTIVES:Electronic health records (EHR) might be a useful resource to study the risk factors and clinical care of people with dementia. We sought to determine the diagnostic validity of dementia captured in linked EHR. METHODS AND FINDINGS:A cohort of adults in linked primary care, hospital, disease registry and mortality records in England, [CALIBER (CArdiovascular disease research using LInked Bespoke studies and Electronic health Records)]. The proportion of individuals with dementia, Alzheimer's disease, vascular and rare dementia in each data source was determined. A comparison was made of symptoms and care between people with dementia and age-, sex- and general practice-matched controls, using conditional logistic regression. The lifetime risk and prevalence of dementia and mortality rates in people with and without dementia were estimated with random-effects Poisson models. There were 47,386 people with dementia: 12,633 with Alzheimer's disease, 9540 with vascular and 1539 with rare dementia. Seventy-four percent of cases had corroborating evidence of dementia. People with dementia were more likely to live in a deprived area (conditional OR 1.26;95%CI:1.20-1.31 most vs least deprived), have documented memory impairment (cOR = 11.97;95%CI:11.24-12.75), falls (cOR = 2.36;95%CI:2.31-2.41), depression (cOR = 2.03; 95%CI:1.98-2.09) or anxiety (cOR = 1.27; 95%CI:1.23-1.32). The lifetime risk of dementia at age 65 was 9.2% (95%CI:9.0%-9.4%), in men and 14.9% (95%CI:14.7%-15.1%) in women. The population prevalence of recorded dementia increased from 0.3% in 2000 to 0.7% in 2010. A higher mortality rate was observed in people with than without dementia (IRR = 1.56;95%CI:1.54-1.58). CONCLUSIONS:Most people with a record of dementia in linked UK EHR had some corroborating evidence for diagnosis. The estimated 10-year risk of dementia was higher than published population-based estimations. EHR are therefore a promising source of data for dementia research."
+30949070,https://doi.org/10.3389/fpsyt.2019.00109,Real World Implementation of a Transdiagnostic Risk Calculator for the Automatic Detection of Individuals at Risk of Psychosis in Clinical Routine: Study Protocol.,"Fusar-Poli P, Oliver D, Spada G, Patel R, Stewart R, Dobson R, McGuire P.","Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.",Frontiers in Psychiatry,2019,"Background: Primary indicated prevention in individuals at-risk for psychosis has the potential to improve the outcomes of this disorder. The ability to detect the majority of at-risk individuals is the main barrier toward extending benefits for the lives of many adolescents and young adults. Current detection strategies are highly inefficient. Only 5% (standalone specialized early detection services) to 12% (youth mental health services) of individuals who will develop a first psychotic disorder can be detected at the time of their at-risk stage. To overcome these challenges a pragmatic, clinically-based, individualized, transdiagnostic risk calculator has been developed to detect individuals at-risk of psychosis in secondary mental health care at scale. This calculator has been externally validated and has demonstrated good prognostic performance. However, it is not known whether it can be used in the real world clinical routine. For example, clinicians may not be willing to adhere to the recommendations made by the transdiagnostic risk calculator. Implementation studies are needed to address pragmatic challenges relating to the real world use of the transdiagnostic risk calculator. The aim of the current study is to provide in-vitro and in-vivo feasibility data to support the implementation of the transdiagnostic risk calculator in clinical routine. Method: This is a study which comprises of two subsequent phases: an in-vitro phase of 1 month and an in-vivo phase of 11 months. The in-vitro phase aims at developing and integrating the transdiagnostic risk calculator in the local electronic health register (primary outcome). The in-vivo phase aims at addressing the clinicians' adherence to the recommendations made by the transdiagnostic risk calculator (primary outcome) and other secondary feasibility parameters that are necessary to estimate the resources needed for its implementation. Discussion: This is the first implementation study for risk prediction models in individuals at-risk for psychosis. Ultimately, successful implementation is the true measure of a prediction model's utility. Therefore, the overall translational deliverable of the current study would be to extend the benefits of primary indicated prevention and improve outcomes of first episode psychosis. This may produce significant social benefits for many adolescents and young adults and their families."
 30819382,https://doi.org/10.1016/j.jchf.2019.01.009,Adverse Drug Reactions to Guideline-Recommended Heart Failure Drugs in Women: A Systematic Review of the Literature.,"Bots SH, Groepenhoff F, Eikendal ALM, Tannenbaum C, Rochon PA, Regitz-Zagrosek V, Miller VM, Day D, Asselbergs FW, den Ruijter HM.","Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Laboratory of Clinical Chemistry and Haematology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.; Faculties of Pharmacy and Medicine, Université de Montréal, Montréal, Canada.; Women's College Research Institute, Women's College Hospital, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.; Institute for Gender in Medicine and Center for Cardiovascular Research, Charite, University Medicine Berlin, Berlin, Germany; DZHK (German Center for Cardiovascular Research), partner site Berlin, Berlin, Germany.; Women's Health Research Center, Mayo Clinic, Rochester, Minnesota.; UniQure, Amsterdam, the Netherlands.; Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; Institute of Cardiovascular Science, Faculty of Popular Health Sciences, University College London, London, United Kingdom; Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom.; Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands. Electronic address: h.m.denruijter-2@umcutrecht.nl.",JACC. Heart failure,2019,"OBJECTIVES:This study sought to summarize all available evidence on sex differences in adverse drug reactions (ADRs) to heart failure (HF) medication. BACKGROUND:Women are more likely to experience ADRs than men, and these reactions may negatively affect women's immediate and long-term health. HF in particular is associated with increased ADR risk because of the high number of comorbidities and older age. However, little is known about ADRs in women with HF who are treated with guideline-recommended drugs. METHODS:A systematic search of PubMed and EMBASE was performed to collect all available information on ADRs to angiotensin-converting enzyme inhibitors, β-blockers, angiotensin II receptor blockers, mineralocorticoid receptor antagonists, ivabradine, and digoxin in both women and men with HF. RESULTS:The search identified 155 eligible records, of which only 11 (7%) reported ADR data for women and men separately. Sex-stratified reporting of ADRs did not increase over the last decades. Six of the 11 studies did not report sex differences. Three studies reported a higher risk of angiotensin-converting enzyme inhibitor-related ADRs in women, 1 study showed higher digoxin-related mortality risk for women, and 1 study reported a higher risk of mineralocorticoid receptor antagonist-related ADRs in men. No sex differences in ADRs were reported for angiotensin II receptor blockers and β-blockers. Sex-stratified data were not available for ivabradine. CONCLUSIONS:These results underline the scarcity of ADR data stratified by sex. The study investigators call for a change in standard scientific practice toward reporting of ADR data for women and men separately."
 31063847,https://doi.org/10.1016/j.bbi.2019.05.009,Transcriptomic analysis of probable asymptomatic and symptomatic alzheimer brains.,"Patel H, Hodges AK, Curtis C, Lee SH, Troakes C, Dobson RJB, Newhouse SJ.","Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK.; Department of Old Age Psychiatry, Maurice Wohl Clinical Neuroscience Institute Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK.; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK; Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK.; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK; Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK.; Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK; London Neurodegenerative Diseases Brain Bank, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK.; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK; Health Data Research UK London, University College London, 222 Euston Road, London, UK; Institute of Health Informatics, University College London, 222 Euston Road, London, UK; The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, 222 Euston Road, London, UK. Electronic address: richard.j.dobson@kcl.ac.uk.; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK; Health Data Research UK London, University College London, 222 Euston Road, London, UK; Institute of Health Informatics, University College London, 222 Euston Road, London, UK; The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, 222 Euston Road, London, UK. Electronic address: stephen.newhouse@kcl.ac.uk.","Brain, behavior, and immunity",2019,"Individuals with intact cognition and neuropathology consistent with Alzheimer's disease (AD) are referred to as asymptomatic AD (AsymAD). These individuals are highly likely to develop AD, yet transcriptomic changes in the brain which might reveal mechanisms for their AD vulnerability are currently unknown. Entorhinal cortex, frontal cortex, temporal cortex and cerebellum tissue from 27 control, 33 AsymAD and 52 AD human brains were microarray expression profiled. Differential expression analysis identified a significant increase of transcriptomic activity in the frontal cortex of AsymAD subjects, suggesting fundamental changes in AD may initially begin within the frontal cortex region prior to AD diagnosis. Co-expression analysis identified an overactivation of the brain ""glutamate-glutamine cycle"", and disturbances in the brain energy pathways in both AsymAD and AD subjects, while the connectivity of key hub genes in this network indicates a shift from an already increased cell proliferation in AsymAD subjects to stress response and removal of amyloidogenic proteins in AD subjects. This study provides new insight into the earliest biological changes occurring in the brain prior to the manifestation of clinical AD symptoms and provides new potential therapeutic targets for early disease intervention."
-31013802,https://doi.org/10.3390/ijerph16081325,Using Patient-Reported Outcomes to Predict Revision Arthroplasty Following Femoral Neck Fracture: Enhancing the Value of Clinical Registries through Data Linkage.,"Ekegren CL, de Steiger R, Edwards ER, Page RS, Hau R, Liew S, Oppy A, Gabbe BJ.","Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. christina.ekegren@monash.edu.; Epworth Hospital, Richmond, VIC 3121, Australia. richard.desteiger@epworth.org.au.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. ere@bigpond.net.au.; Department of Orthopaedics, University Hospital Geelong, Geelong, VIC 3220, Australia. richard.page@deakin.edu.au.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. raphaelhau@hotmail.com.; Department of Orthopaedic Surgery, Alfred Hospital, Melbourne, VIC 3004, Australia. s.liew@alfred.org.au.; Epworth Hospital, Richmond, VIC 3121, Australia. andrewoppy@me.com.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. belinda.gabbe@monash.edu.",International Journal of Environmental Research and Public Health,2019,"The aim of this study was to determine the association between patient-reported outcome measures (PROMs) six months following femoral neck fracture after a low fall and future arthroplasty, and the factors associated with this. Six-month post-fracture PROMs were collected from the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR) for patients aged >55 years who were admitted for a femoral neck fracture after a low fall between March 2007 and June 2015. These cases were linked with those registered by Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) up to October 2016. Multivariable analysis was performed using a Cox proportional hazards model to determine factors associated with future arthroplasty, including six-month PROMs. Of the 7077 hip fracture patients registered by VOTOR during the study period, 2325 met the inclusion criteria. Internal fixation being used for the initial hip fracture surgery, being younger and having no pre-injury disability were all independently associated with future revision or conversion to arthroplasty. Out of all PROMs, reporting pain and discomfort six months post-fracture was associated with a 9.5-fold increase in the risk of future arthroplasty (95% CI: 3.81, 23.67). The value of clinical registries can be enhanced via data linkage, in this case by using PROMs to predict arthroplasty following femoral neck fracture."
+31013802,https://doi.org/10.3390/ijerph16081325,Using Patient-Reported Outcomes to Predict Revision Arthroplasty Following Femoral Neck Fracture: Enhancing the Value of Clinical Registries through Data Linkage.,"Ekegren CL, de Steiger R, Edwards ER, Page RS, Hau R, Liew S, Oppy A, Gabbe BJ.","Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. christina.ekegren@monash.edu.; Epworth Hospital, Richmond, VIC 3121, Australia. richard.desteiger@epworth.org.au.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. ere@bigpond.net.au.; Department of Orthopaedics, University Hospital Geelong, Geelong, VIC 3220, Australia. richard.page@deakin.edu.au.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. raphaelhau@hotmail.com.; Department of Orthopaedic Surgery, Alfred Hospital, Melbourne, VIC 3004, Australia. s.liew@alfred.org.au.; Epworth Hospital, Richmond, VIC 3121, Australia. andrewoppy@me.com.; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. belinda.gabbe@monash.edu.",International journal of environmental research and public health,2019,"The aim of this study was to determine the association between patient-reported outcome measures (PROMs) six months following femoral neck fracture after a low fall and future arthroplasty, and the factors associated with this. Six-month post-fracture PROMs were collected from the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR) for patients aged >55 years who were admitted for a femoral neck fracture after a low fall between March 2007 and June 2015. These cases were linked with those registered by Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) up to October 2016. Multivariable analysis was performed using a Cox proportional hazards model to determine factors associated with future arthroplasty, including six-month PROMs. Of the 7077 hip fracture patients registered by VOTOR during the study period, 2325 met the inclusion criteria. Internal fixation being used for the initial hip fracture surgery, being younger and having no pre-injury disability were all independently associated with future revision or conversion to arthroplasty. Out of all PROMs, reporting pain and discomfort six months post-fracture was associated with a 9.5-fold increase in the risk of future arthroplasty (95% CI: 3.81, 23.67). The value of clinical registries can be enhanced via data linkage, in this case by using PROMs to predict arthroplasty following femoral neck fracture."
+31234639,https://doi.org/10.1161/circulationaha.118.038814,Use of Genetic Variants Related to Antihypertensive Drugs to Inform on Efficacy and Side Effects.,"Gill D, Georgakis MK, Koskeridis F, Jiang L, Feng Q, Wei WQ, Theodoratou E, Elliott P, Denny JC, Malik R, Evangelou E, Dehghan A, Dichgans M, Tzoulaki I.","Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom.; Institute for Stroke and Dementia Research, University Hospital, and Graduate School for Systemic Neurosciences, Ludwig-Maximilians-Universität LMU, Munich, Germany.; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Greece.; Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN.; Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN.; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.; Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, United Kingdom.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom; Medical Research Council-Public Health England Centre for Environment, School of Public Health, Imperial College London, United Kingdom; Imperial Biomedical Research Centre, Imperial College London and Imperial College NHS Healthcare Trust, United Kingdom; UK Dementia Research Institute at Imperial College London, United Kingdom; Health Data Research UK-London, United Kingdom.; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.; Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität LMU, Munich, Germany.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Greece.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom; Medical Research Council-Public Health England Centre for Environment, School of Public Health, Imperial College London, United Kingdom; UK Dementia Research Institute at Imperial College London, United Kingdom.; Institute for Stroke and Dementia Research, University Hospital, Ludwig-MaximiliansUniversität LMU, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Germany; German Center for Neurodegenerative Diseases (DZNE, Munich), Germany.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Greece; Medical Research Council-Public Health England Centre for Environment, School of Public Health, Imperial College London, United Kingdom; UK Dementia Research Institute at Imperial College London, United Kingdom.",Circulation,2019,"BACKGROUND:Drug effects can be investigated through natural variation in the genes for their protein targets. The present study aimed to use this approach to explore the potential side effects and repurposing potential of antihypertensive drugs, which are among the most commonly used medications worldwide. METHODS:Genetic proxies for the effect of antihypertensive drug classes were identified as variants in the genes for the corresponding targets that associated with systolic blood pressure at genome-wide significance. Mendelian randomization estimates for drug effects on coronary heart disease and stroke risk were compared with randomized, controlled trial results. Phenome-wide association study in the UK Biobank was performed to identify potential side effects and repurposing opportunities, with findings investigated in the Vanderbilt University biobank (BioVU) and in observational analysis of the UK Biobank. RESULTS:Suitable genetic proxies for angiotensin-converting enzyme inhibitors, β-blockers, and calcium channel blockers (CCBs) were identified. Mendelian randomization estimates for their effect on coronary heart disease and stroke risk, respectively, were comparable to results from randomized, controlled trials against placebo. A phenome-wide association study in the UK Biobank identified an association of the CCB standardized genetic risk score with increased risk of diverticulosis (odds ratio, 1.02 per standard deviation increase; 95% CI, 1.01-1.04), with a consistent estimate found in BioVU (odds ratio, 1.01; 95% CI, 1.00-1.02). Cox regression analysis of drug use in the UK Biobank suggested that this association was specific to nondihydropyridine CCBs (hazard ratio 1.49 considering thiazide diuretic agents as a comparator; 95% CI, 1.04-2.14) but not dihydropyridine CCBs (hazard ratio, 1.04; 95% CI, 0.83-1.32). CONCLUSIONS:Genetic variants can be used to explore the efficacy and side effects of antihypertensive medications. The identified potential effect of nondihydropyridine CCBs on diverticulosis risk could have clinical implications and warrants further investigation."
+31226389,https://doi.org/10.1016/j.jhep.2019.05.032,Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration.,"Wilman HR, Parisinos CA, Atabaki-Pasdar N, Kelly M, Louise Thomas E, Neubauer S, IMI DIRECT Consortium.","Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, U.K. and Perspectum Diagnostics Ltd., Oxford, UK. Electronic address: h.wilman@westminster.ac.uk.; Institute of Health Informatics, Faculty of Population Health Sciences, University College London, London, UK. Electronic address: c.parisinos@ucl.ac.uk.; Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, Malmö, Sweden. Electronic address: naimeh.atabaki_pasdar@med.lu.se.; Perspectum Diagnostics Ltd., Oxford, UK. Electronic address: matt.kelly@perspectum-diagnostics.com.; Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK. Electronic address: l.thomas3@westminster.ac.uk.; Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK and Perspectum Diagnostics Ltd., Oxford, UK. Electronic address: stefan.neubauer@perspectum.com.",Journal of hepatology,2019,"BACKGROUND & AIMS:Excess liver iron content is common and is linked to hepatic and extrahepatic disease risk. We aimed to identify genetic variants influencing liver iron content and use genetics to understand its link to other traits and diseases. METHODS:First, we performed a genome-wide association study (GWAS) in 8,289 individuals in UK Biobank with MRI quantified liver iron, and validated our findings in an independent cohort (n=1,513 from IMI DIRECT). Second, we used Mendelian randomisation to test the causal effects of 29 predominantly metabolic traits on liver iron content. Third, we tested phenome-wide associations between liver iron variants and 770 anthropometric traits and diseases. RESULTS:We identified three independent genetic variants (rs1800562 (C282Y) and rs1799945 (H63D) in HFE and rs855791 (V736A) in TMPRSS6) associated with liver iron content that reached the GWAS significance threshold (p < 5x10-8). The two HFE variants account for ∼85% of all cases of hereditary haemochromatosis. Mendelian randomisation analysis provided evidence that higher central obesity plays a causal role in increased liver iron content. Phenome-wide association analysis demonstrated shared aetiopathogenic mechanisms for elevated liver iron, high blood pressure, cirrhosis, malignancies, neuropsychiatric and rheumatological conditions, while also highlighting inverse associations with anaemias, lipidaemias and ischaemic heart disease. CONCLUSION:Our study provides genetic evidence that mechanisms underlying higher liver iron content are likely systemic rather than organ specific, that higher central obesity is causally associated with higher liver iron, and that liver iron shares common aetiology with multiple metabolic and non-metabolic diseases. LAY SUMMARY:Excess liver iron content is common and is associated with liver diseases and metabolic diseases including diabetes, high blood pressure, and heart disease. We find that three genetic variants are linked to increased risk of developing higher liver iron content. We show that the same genetic variants are linked to higher risk of many diseases, but they may also be associated with some health advantages. Finally, we use genetic variants associated with waist-to-hip ratio as a tool to show that central obesity is causally associated with increased liver iron content."
 30497795,https://doi.org/10.1016/S0140-6736(18)32207-4,Changes in health in the countries of the UK and 150 English Local Authority areas 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.,"Steel N, Ford JA, Newton JN, Davis ACJ, Vos T, Naghavi M, Glenn S, Hughes A, Dalton AM, Stockton D, Humphreys C, Dallat M, Schmidt J, Flowers J, Fox S, Abubakar I, Aldridge RW, Baker A, Brayne C, Brugha T, Capewell S, Car J, Cooper C, Ezzati M, Fitzpatrick J, Greaves F, Hay R, Hay S, Kee F, Larson HJ, Lyons RA, Majeed A, McKee M, Rawaf S, Rutter H, Saxena S, Sheikh A, Smeeth L, Viner RM, Vollset SE, Williams HC, Wolfe C, Woolf A, Murray CJL.","University of East Anglia, Norwich, UK. Electronic address: n.steel@uea.ac.uk.; University of East Anglia, Norwich, UK.; Public Health England, London, UK.; AD CAVE Solutions Ltd, London, UK; Imperial College London, London, UK.; Institute for Health Metrics and Evaluation, Seattle, WA, USA.; Institute for Health Metrics and Evaluation, Seattle, WA, USA.; Institute for Health Metrics and Evaluation, Seattle, WA, USA.; Public Health England, Oxford, UK.; University of East Anglia, Norwich, UK.; NHS Health Scotland, Edinburgh, UK.; Public Health Wales, Carmarthen, UK.; Public Health Agency, Belfast, UK.; Public Health England, London, UK.; Public Health England, London, UK.; Public Health England, London, UK.; University College London, London, UK.; University College London, London, UK.; Public Health England, London, UK.; Cambridge Institute of Public Health, University of Cambridge, Cambridge, UK.; Department of Health Sciences, College of Life Sciences, University of Leicester, Leicester, UK.; Department of Public Health & Policy, Institute of Psychology, Health & Society, University of Liverpool, Liverpool, UK.; Imperial College London, London, UK; Centre for Population Health Sciences, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.; MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK; NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK; NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.; Imperial College London, London, UK.; Public Health England, London, UK.; Public Health England, London, UK; Imperial College London, London, UK.; King's College London, London, UK.; Institute for Health Metrics and Evaluation, Seattle, WA, USA.; UKCRC Centre of Excellence for Public Health Research (NI), Queens University of Belfast, Belfast, UK.; Institute for Health Metrics and Evaluation, Seattle, WA, USA; London School of Hygiene & Tropical Medicine, London, UK.; Health Data Research UK, Swansea University, Swansea, UK.; Imperial College London, London, UK.; London School of Hygiene & Tropical Medicine, London, UK.; Imperial College London, London, UK.; University of Bath, Bath, UK.; Imperial College London, London, UK.; Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.; London School of Hygiene & Tropical Medicine, London, UK.; University College London, London, UK.; Institute for Health Metrics and Evaluation, Seattle, WA, USA.; Centre of Evidence-Based Dermatology, Queen's Medical Centre, Nottingham University Hospitals NHS Trust, Nottingham, UK.; King's College London, London, UK.; Bone and Joint Research Group, Royal Cornwall Hospital, Truro, UK.; Institute for Health Metrics and Evaluation, Seattle, WA, USA.","Lancet (London, England)",2018,"BACKGROUND:Previous studies have reported national and regional Global Burden of Disease (GBD) estimates for the UK. Because of substantial variation in health within the UK, action to improve it requires comparable estimates of disease burden and risks at country and local levels. The slowdown in the rate of improvement in life expectancy requires further investigation. We use GBD 2016 data on mortality, causes of death, and disability to analyse the burden of disease in the countries of the UK and within local authorities in England by deprivation quintile. METHODS:We extracted data from the GBD 2016 to estimate years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), and attributable risks from 1990 to 2016 for England, Scotland, Wales, Northern Ireland, the UK, and 150 English Upper-Tier Local Authorities. We estimated the burden of disease by cause of death, condition, year, and sex. We analysed the association between burden of disease and socioeconomic deprivation using the Index of Multiple Deprivation. We present results for all 264 GBD causes of death combined and the leading 20 specific causes, and all 84 GBD risks or risk clusters combined and 17 specific risks or risk clusters. FINDINGS:The leading causes of age-adjusted YLLs in all UK countries in 2016 were ischaemic heart disease, lung cancers, cerebrovascular disease, and chronic obstructive pulmonary disease. Age-standardised rates of YLLs for all causes varied by two times between local areas in England according to levels of socioeconomic deprivation (from 14 274 per 100 000 population [95% uncertainty interval 12 791-15 875] in Blackpool to 6888 [6145-7739] in Wokingham). Some Upper-Tier Local Authorities, particularly those in London, did better than expected for their level of deprivation. Allowing for differences in age structure, more deprived Upper-Tier Local Authorities had higher attributable YLLs for most major risk factors in the GBD. The population attributable fractions for all-cause YLLs for individual major risk factors varied across Upper-Tier Local Authorities. Life expectancy and YLLs have improved more slowly since 2010 in all UK countries compared with 1990-2010. In nine of 150 Upper-Tier Local Authorities, YLLs increased after 2010. For attributable YLLs, the rate of improvement slowed most substantially for cardiovascular disease and breast, colorectal, and lung cancers, and showed little change for Alzheimer's disease and other dementias. Morbidity makes an increasing contribution to overall burden in the UK compared with mortality. The age-standardised UK DALY rate for low back and neck pain (1795 [1258-2356]) was higher than for ischaemic heart disease (1200 [1155-1246]) or lung cancer (660 [642-679]). The leading causes of ill health (measured through YLDs) in the UK in 2016 were low back and neck pain, skin and subcutaneous diseases, migraine, depressive disorders, and sense organ disease. Age-standardised YLD rates varied much less than equivalent YLL rates across the UK, which reflects the relative scarcity of local data on causes of ill health. INTERPRETATION:These estimates at local, regional, and national level will allow policy makers to match resources and priorities to levels of burden and risk factors. Improvement in YLLs and life expectancy slowed notably after 2010, particularly in cardiovascular disease and cancer, and targeted actions are needed if the rate of improvement is to recover. A targeted policy response is also required to address the increasing proportion of burden due to morbidity, such as musculoskeletal problems and depression. Improving the quality and completeness of available data on these causes is an essential component of this response. FUNDING:Bill & Melinda Gates Foundation and Public Health England."
 30898389,https://doi.org/10.1016/j.injury.2019.03.003,Potentially preventable trauma deaths: A retrospective review.,"Beck B, Smith K, Mercier E, Bernard S, Jones C, Meadley B, Clair TS, Jennings PA, Nehme Z, Burke M, Bassed R, Fitzgerald M, Judson R, Teague W, Mitra B, Mathew J, Buck A, Varma D, Gabbe B, Bray J, McLellan S, Ford J, Siedenburg J, Cameron P.","Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Faculty of Medicine, Laval University, Quebec City, Quebec, Canada. Electronic address: ben.beck@monash.edu.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Centre for Research and Evaluation, Ambulance Victoria, Victoria, Australia; Department of Community Emergency Health and Paramedic Practice, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Faculty of Medicine, Laval University, Quebec City, Quebec, Canada.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Centre for Research and Evaluation, Ambulance Victoria, Victoria, Australia; The Intensive Care Unit, The Alfred Hospital.; Ambulance Victoria, Victoria, Australia.; Department of Community Emergency Health and Paramedic Practice, Monash University, Victoria, Australia; Ambulance Victoria, Victoria, Australia.; Department of Community Emergency Health and Paramedic Practice, Monash University, Victoria, Australia; Ambulance Victoria, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Department of Community Emergency Health and Paramedic Practice, Monash University, Victoria, Australia; Ambulance Victoria, Victoria, Australia; Emergency and Trauma Centre, The Alfred, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Centre for Research and Evaluation, Ambulance Victoria, Victoria, Australia; Department of Community Emergency Health and Paramedic Practice, Monash University, Victoria, Australia; Ambulance Victoria, Victoria, Australia.; Victorian Institute of Forensic Medicine, Victoria, Australia.; Victorian Institute of Forensic Medicine, Victoria, Australia; Department of Forensic Medicine, Monash University, Victoria, Australia.; Trauma Service, The Alfred, Victoria, Australia; National Trauma Research Institute, Victoria, Australia.; General Surgery, The Royal Melbourne Hospital, Victoria, Australia; Department of Surgery, The University of Melbourne, Victoria, Australia.; Trauma Service, The Royal Children's Hospital, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia; Surgical Research Group, Murdoch Children's Research Institute, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; National Trauma Research Institute, Victoria, Australia; Emergency and Trauma Centre, The Alfred, Victoria, Australia.; Trauma Service, The Alfred, Victoria, Australia; National Trauma Research Institute, Victoria, Australia; Emergency and Trauma Centre, The Alfred, Victoria, Australia.; Emergency Department, Royal Darwin Hospital, Northern Territory, Australia.; Department of Surgery, The University of Melbourne, Victoria, Australia; Radiology, The Alfred, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Health Data Research UK, Swansea University Medical School, Swansea University, UK.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; Prehospital, Resuscitation and Emergency Care Research Unit (PRECRU), School of Nursing, Midwifery and Paramedicine, Curtin University, Perth, Western Australia, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia.; Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; National Trauma Research Institute, Victoria, Australia; Emergency and Trauma Centre, The Alfred, Victoria, Australia.",Injury,2019,"BACKGROUND:Reviewing prehospital trauma deaths provides an opportunity to identify system improvements that may reduce trauma mortality. The objective of this study was to identify the number and rate of potentially preventable trauma deaths through expert panel reviews of prehospital and early in-hospital trauma deaths. METHODS:We conducted a retrospective review of prehospital and early in-hospital (<24 h) trauma deaths following a traumatic out-of-hospital cardiac arrest that were attended by Ambulance Victoria (AV) in the state of Victoria, Australia, between 2008 and 2014. Expert panels were used to review cases that had resuscitation attempted by paramedics and underwent a full autopsy. Patients with a mechanism of hanging, drowning or those with anatomical injuries deemed to be unsurvivable were excluded. RESULTS:Of the 1183 cases that underwent full autopsies, resuscitation was attempted by paramedics in 336 (28%) cases. Of these, 113 cases (34%) were deemed to have potentially survivable injuries and underwent expert panel review. There were 90 (80%) deaths that were not preventable, 19 (17%) potentially preventable deaths and 4 (3%) preventable deaths. Potentially preventable or preventable deaths represented 20% of those cases that underwent review and 7% of cases that had attempted resuscitation. CONCLUSIONS:The number of potentially preventable or preventable trauma deaths in the pre-hospital and early in-hospital resuscitation phase was low. Specific circumstances were identified in which the trauma system could be further improved."
 30487518,https://doi.org/10.1038/s41467-018-07345-0,Interethnic analyses of blood pressure loci in populations of East Asian and European descent.,"Takeuchi F, Akiyama M, Matoba N, Katsuya T, Nakatochi M, Tabara Y, Narita A, Saw WY, Moon S, Spracklen CN, Chai JF, Kim YJ, Zhang L, Wang C, Li H, Li H, Wu JY, Dorajoo R, Nierenberg JL, Wang YX, He J, Bennett DA, Takahashi A, Momozawa Y, Hirata M, Matsuda K, Rakugi H, Nakashima E, Isono M, Shirota M, Hozawa A, Ichihara S, Matsubara T, Yamamoto K, Kohara K, Igase M, Han S, Gordon-Larsen P, Huang W, Lee NR, Adair LS, Hwang MY, Lee J, Chee ML, Sabanayagam C, Zhao W, Liu J, Reilly DF, Sun L, Huo S, Edwards TL, Long J, Chang LC, Chen CH, Yuan JM, Koh WP, Friedlander Y, Kelly TN, Bin Wei W, Xu L, Cai H, Xiang YB, Lin K, Clarke R, Walters RG, Millwood IY, Li L, Chambers JC, Kooner JS, Elliott P, van der Harst P, International Genomics of Blood Pressure (iGEN-BP) Consortium, Chen Z, Sasaki M, Shu XO, Jonas JB, He J, Heng CK, Chen YT, Zheng W, Lin X, Teo YY, Tai ES, Cheng CY, Wong TY, Sim X, Mohlke KL, Yamamoto M, Kim BJ, Miki T, Nabika T, Yokota M, Kamatani Y, Kubo M, Kato N.","Medical Genomics Center, National Center for Global Health and Medicine, Tokyo, 162-8655, Japan.; Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.; Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.; Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan.; Data Coordinating Center, Department of Advanced Medicine, Nagoya University Hospital, Nagoya, 466-8560, Japan.; Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8507, Japan.; Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan.; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.; Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 363-951, Republic of Korea.; Department of Genetics, University of North Carolina, Chapel Hill, NC 27514, USA.; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.; Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 363-951, Republic of Korea.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore.; Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672, Singapore.; CAS Key Laboratory of Nutrition, Metabolism and Food safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.; State Key Laboratory of Oncogene and Related Genes and Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China.; Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan.; Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672, Singapore.; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.; Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China.; Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN 37203-1738, USA.; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.; Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.; Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.; Institute of Medical Science, The University of Tokyo, Tokyo, 108-8639, Japan.; Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, 277-8561, Japan.; Department of Geriatric and General Medicine, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan.; Division of Endocrinology and Diabetes, Department of Internal Medicine, Nagoya University Graduate School of Medicine, Nagoya, 466-8550, Japan.; Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, 162-8655, Japan.; Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan.; Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan.; Department of Environmental and Preventive Medicine, Jichi Medical University School of Medicine, Shimotsuke, 329-0498, Japan.; Department of Internal Medicine, School of Dentistry, Aichi Gakuin University, Nagoya, 470-0195, Japan.; Department of Medical Biochemistry, Kurume University School of Medicine, Kurume, 830-0011, Japan.; Faculty of Collaborative Regional Innovation, Ehime University, Matsuyama, 790-8577, Ehime, Japan.; Department of Geriatric Medicine, Ehime University Graduate School of Medicine, Toon, 791-0295, Ehime, Japan.; Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 363-951, Republic of Korea.; Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.; Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center and Shanghai Industrial Technology Institute (SITI), Shanghai, 201203, China.; USC-Office of Population Studies Foundation, University of San Carlos, Cebu City, 6000, Philippines.; Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.; Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 363-951, Republic of Korea.; Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 363-951, Republic of Korea.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore.; Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672, Singapore.; Merck Sharp Dohme Corp, Kenilworth, NJ 07033, USA.; CAS Key Laboratory of Nutrition, Metabolism and Food safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.; CAS Key Laboratory of Nutrition, Metabolism and Food safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.; Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN 37203-1738, USA.; Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN 37203-1738, USA.; Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan.; Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan.; Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.; Unit of Epidemiology, Hebrew University-Hadassah Braun School of Public Health, Jerusalem, P.O. Box 12272, Israel.; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.; Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China.; Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China.; Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN 37203-1738, USA.; State Key Laboratory of Oncogene and Related Genes and Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China.; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.; Chinese Academy of Medical Sciences, Beijing, 100006, China.; Department of Epidemiology and Biostatistics, Imperial College London, London, SW7 2AZ, UK.; National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK.; Medical Research Council-Public Health England (MRC-PHE) Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK.; Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, Netherlands.; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.; Iwate Tohoku Medical Megabank Organization, Iwate, 028-3694, Japan.; Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN 37203-1738, USA.; Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China.; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.; Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore.; Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan.; Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN 37203-1738, USA.; CAS Key Laboratory of Nutrition, Metabolism and Food safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore.; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.; Department of Genetics, University of North Carolina, Chapel Hill, NC 27514, USA.; Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan.; Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 363-951, Republic of Korea.; Department of Geriatric Medicine, Ehime University Graduate School of Medicine, Toon, 791-0295, Ehime, Japan.; Department of Functional Pathology, Shimane University Faculty of Medicine, Izumo, 693-0021, Japan.; Department of Genome Science, School of Dentistry, Aichi Gakuin University, Nagoya, 464-8650, Japan.; Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.; RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.; Medical Genomics Center, National Center for Global Health and Medicine, Tokyo, 162-8655, Japan. nokato@ri.ncgm.go.jp.",Nature communications,2018,"Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, we perform a multi-stage genome-wide association study for BP (max N = 289,038) principally in East Asians and meta-analysis in East Asians and Europeans. We report 19 new genetic loci and ancestry-specific BP variants, conforming to a common ancestry-specific variant association model. At 10 unique loci, distinct non-rare ancestry-specific variants colocalize within the same linkage disequilibrium block despite the significantly discordant effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect-sizes is 0.898 and 0.851 for systolic and diastolic BP, respectively. Some of the ancestry-specific association signals are also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in ethnic differences in complex traits such as BP."