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Factors associated with COVID-19-related death using OpenSAFELY.
Williamson, Elizabeth J; Walker, Alex J; Bhaskaran, Krishnan; Bacon, Seb; Bates, Chris; Morton, Caroline E; Curtis, Helen J; Mehrkar, Amir; Evans, David; Inglesby, Peter; Cockburn, Jonathan; McDonald, Helen I; MacKenna, Brian; Tomlinson, Laurie; Douglas, Ian J; Rentsch, Christopher T; Mathur, Rohini; Wong, Angel Y S; Grieve, Richard; Harrison, David; Forbes, Harriet; Schultze, Anna; Croker, Richard; Parry, John; Hester, Frank; Harper, Sam; Perera, Rafael; Evans, Stephen J W; Smeeth, Liam; Goldacre, Ben.
  • Williamson EJ; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
  • Walker AJ; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Bhaskaran K; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
  • Bacon S; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Bates C; TPP, Horsforth, UK.
  • Morton CE; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Curtis HJ; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Mehrkar A; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Evans D; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Inglesby P; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Cockburn J; TPP, Horsforth, UK.
  • McDonald HI; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
  • MacKenna B; NIHR Health Protection Research Unit in Immunisation, London, UK.
  • Tomlinson L; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Douglas IJ; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
  • Rentsch CT; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
  • Mathur R; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
  • Wong AYS; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
  • Grieve R; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
  • Harrison D; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
  • Forbes H; Intensive Care National Audit and Research Centre (ICNARC), London, UK.
  • Schultze A; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
  • Croker R; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
  • Parry J; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Hester F; TPP, Horsforth, UK.
  • Harper S; TPP, Horsforth, UK.
  • Perera R; TPP, Horsforth, UK.
  • Evans SJW; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Smeeth L; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
  • Goldacre B; London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
Nature ; 584(7821): 430-436, 2020 08.
Article in English | MEDLINE | ID: covidwho-981546
ABSTRACT
Coronavirus disease 2019 (COVID-19) has rapidly affected mortality worldwide1. There is unprecedented urgency to understand who is most at risk of severe outcomes, and this requires new approaches for the timely analysis of large datasets. Working on behalf of NHS England, we created OpenSAFELY-a secure health analytics platform that covers 40% of all patients in England and holds patient data within the existing data centre of a major vendor of primary care electronic health records. Here we used OpenSAFELY to examine factors associated with COVID-19-related death. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19-related deaths. COVID-19-related death was associated with being male (hazard ratio (HR) 1.59 (95% confidence interval 1.53-1.65)); greater age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared with people of white ethnicity, Black and South Asian people were at higher risk, even after adjustment for other factors (HR 1.48 (1.29-1.69) and 1.45 (1.32-1.58), respectively). We have quantified a range of clinical factors associated with COVID-19-related death in one of the largest cohort studies on this topic so far. More patient records are rapidly being added to OpenSAFELY, we will update and extend our results regularly.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Betacoronavirus Type of study: Cohort study / Observational study / Prognostic study Limits: Adolescent / Adult / Aged / Female / Humans / Male / Middle aged / Young adult Language: English Journal: Nature Year: 2020 Document Type: Article Affiliation country: S41586-020-2521-4

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Betacoronavirus Type of study: Cohort study / Observational study / Prognostic study Limits: Adolescent / Adult / Aged / Female / Humans / Male / Middle aged / Young adult Language: English Journal: Nature Year: 2020 Document Type: Article Affiliation country: S41586-020-2521-4