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COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records.
Thygesen, Johan H; Tomlinson, Christopher; Hollings, Sam; Mizani, Mehrdad A; Handy, Alex; Akbari, Ashley; Banerjee, Amitava; Cooper, Jennifer; Lai, Alvina G; Li, Kezhi; Mateen, Bilal A; Sattar, Naveed; Sofat, Reecha; Torralbo, Ana; Wu, Honghan; Wood, Angela; Sterne, Jonathan A C; Pagel, Christina; Whiteley, William N; Sudlow, Cathie; Hemingway, Harry; Denaxas, Spiros.
Afiliación
  • Thygesen JH; Institute of Health Informatics, University College London, London, UK.
  • Tomlinson C; Institute of Health Informatics, University College London, London, UK; UK Research and Innovation Centre for Doctoral Training in AI-enabled Healthcare Systems, University College London, London, UK; University College London Hospitals Biomedical Research Centre, University College London, London,
  • Hollings S; NHS Digital, Leeds, UK.
  • Mizani MA; Institute of Health Informatics, University College London, London, UK.
  • Handy A; Institute of Health Informatics, University College London, London, UK.
  • Akbari A; Population Data Science, Swansea University, Swansea, UK.
  • Banerjee A; Institute of Health Informatics, University College London, London, UK.
  • Cooper J; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • Lai AG; Institute of Health Informatics, University College London, London, UK.
  • Li K; Institute of Health Informatics, University College London, London, UK; UK Research and Innovation Centre for Doctoral Training in AI-enabled Healthcare Systems, University College London, London, UK.
  • Mateen BA; Institute of Health Informatics, University College London, London, UK; The Wellcome Trust, London, UK.
  • Sattar N; Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
  • Sofat R; Institute of Health Informatics, University College London, London, UK; Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; British Heart Foundation Data Science Centre, Health Data Research UK, London, UK.
  • Torralbo A; Institute of Health Informatics, University College London, London, UK.
  • Wu H; Institute of Health Informatics, University College London, London, UK.
  • Wood A; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, and Cambridge Centre for AI in Medicine, University of Cambridge, Cambridge, UK.
  • Sterne JAC; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • Pagel C; Clinical Operational Research Unit, University College London, London, UK.
  • Whiteley WN; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
  • Sudlow C; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; British Heart Foundation Data Science Centre, Health Data Research UK, London, UK; Health Data Research UK, London, UK.
  • Hemingway H; Institute of Health Informatics, University College London, London, UK; University College London Hospitals Biomedical Research Centre, University College London, London, UK; Health Data Research UK, London, UK.
  • Denaxas S; Institute of Health Informatics, University College London, London, UK; British Heart Foundation Research Accelerator, University College London, London, UK; University College London Hospitals Biomedical Research Centre, University College London, London, UK; British Heart Foundation Data Science C
Lancet Digit Health ; 4(7): e542-e557, 2022 07.
Article en En | MEDLINE | ID: mdl-35690576
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Etiology_studies / Guideline / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Europa Idioma: En Revista: Lancet Digit Health Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Etiology_studies / Guideline / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Europa Idioma: En Revista: Lancet Digit Health Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido