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OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients
Open accessPreprint — published as 10.1038/s41586-020-2521-4 · Paper page
Abstract
Background: Establishing who is at risk from a novel rapidly arising cause of death, and why, requires a new approach to epidemiological research with very large datasets and timely data. Working on behalf of NHS England we therefore set out to deliver a secure and pseudonymised analytics platform inside the data centre of a major primary care electronic health records vendor establishing coverage across detailed primary care records for a substantial proportion of all patients in England. The following results are preliminary. Data sources: Primary care electronic health records managed by the electronic health record vendor TPP, pseudonymously linked to patient-level data from the COVID-19 Patient Notification System (CPNS) for death of hospital inpatients with confirmed COVID-19, using the new OpenSAFELY platform. Population: 17,425,445 adults. Time period: 1st Feb 2020 to 25th April 2020. Primary outcome: Death in hospital among people with confirmed COVID-19. Methods: Cohort study analysed by Cox-regression to generate hazard ratios: age and sex adjusted, and multiply adjusted for co-variates selected prospectively on the basis of clinical interest and prior findings. Results: There were 5683 deaths attributed to COVID-19. In summary after full adjustment, death from COVID-19 was strongly associated with: being male (hazard ratio 1.99, 95%CI 1.88-2.10); older age and deprivation (both with a strong gradient); uncontrolled diabetes (HR 2.36 95% CI 2.18-2.56); severe asthma (HR 1.25 CI 1.08-1.44); and various other prior medical conditions. Compared to people with ethnicity recorded as white, black people were at higher risk of death, with only partial attenuation in hazard ratios from the fully adjusted model (age-sex adjusted HR 2.17 95% CI 1.84-2.57; fully adjusted HR 1.71 95% CI 1.44-2.02); with similar findings for Asian people (age-sex adjusted HR 1.95 95% CI 1.73-2.18; fully adjusted HR 1.62 95% CI 1.431.82). Conclusions: We have quantified a range of clinical risk factors for death from COVID-19, some of which were not previously well characterised, in the largest cohort study conducted by any country to date. People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required. Deprivation is also a major risk factor with, again, little of the excess risk explained by co-morbidity or other risk factors. The findings for clinical risk factors are concordant with policies in the UK for protecting those at highest risk. Our OpenSAFELY platform is rapidly adding further NHS patients’ records; we will update and extend these results regularly.
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“However, most associations observed between baseline characteristics and mortality or intubation are in line with prior epidemiological studies [17,19].”
From Association between antidepressant use and reduced risk of intubation or death in hospitalized patients with COVID-19: results from an observational study (2021) · cites this paper as [17]
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Metadata
- Authors
- Collaborative, T. O., Williamson, E., Walker, A. J., Bhaskaran, K., Bacon, S., Bates, C., Morton, C. E., Curtis, H. J., Mehrkar, A., Evans, D., Inglesby, P., Cockburn, J., McDonald, H. I., MacKenna, B., Tomlinson, L., Douglas, I. J., Rentsch, C. T., Mathur, R., Wong, A., Grieve, R., Harrison, D., Forbes, H., Schultze, A., Croker, R., Parry, J., Hester, F., Harper, S., Perera, R., Evans, S., Smeeth, L., & Goldacre, B.
- Affiliations
- London School of Hygiene & Tropical Medicine (GB)
- University of Oxford (GB)
- National Institute for Health and Care Research (GB)
- Corresponding author
- Goldacre, Ben
- ORCID
- Williamson, Elizabeth
- Walker, Alex J
- Bhaskaran, Krishnan
- Bacon, Seb
- Morton, Caroline E
- Curtis, Helen J
- Inglesby, Peter
- Cockburn, Jonathan
- McDonald, Helen I
- MacKenna, Brian
- Tomlinson, Laurie
- Douglas, Ian J
- Rentsch, Christopher T
- Mathur, Rohini
- Wong, Angel
- Grieve, Richard
- Harrison, David
- Schultze, Anna
- Croker, Richard
- Hester, Frank
- Perera, Raf
- Evans, Stephen
- Smeeth, Liam
- Goldacre, Ben
- Venue
- Nature
- Publisher
- openRxiv
- Published
- 2020-05-07
- Volume
- 584
- Issue
- 7821
- Pages
- 430-436
- ISSN
- 0028-0836 (ISSN-L)
- PMC
- PMC7611074
- OpenAlex
- W3047144258
- Cited by
- 6,674
- References
- 32
- Citations by year
- 2026: 176 · 2025: 303 · 2024: 698 · 2023: 904 · 2022: 1505 · 2021: 2173 · 2020: 908
- FWCI
- 179.94
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature (publishedVersion)
- medRxiv (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- PubMed Central (acceptedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Queen Mary Research Online (Queen Mary University of London) (submittedVersion)
- Funders
- London School of Hygiene and Tropical Medicine
- Wellcome Trust (107731/Z/15/Z, 201375/Z/16/Z, 201375, 107731)
- UK Research and Innovation
- National Institute for Health Research Health Protection Research Unit
- National Institute for Health and Care Research
- British Heart Foundation (FS/19/19/34175)
- Department of Health and Social Care
- Royal Society
- Diabetes UK
- Public Health England
- Medical Research Council (MR/S003940/1)
- NIHR Oxford Biomedical Research Centre
- National Institute for Health and Care Research Applied Research Collaboration Oxford and Thames Valley
- Topics
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Medicine › Oncology › COVID-19 and healthcare impacts
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Keywords
- COVID-19 pandemic, COVID-19 mortality, risk factors, OpenSAFELY, primary care electronic health records, sex differences, age, socioeconomic deprivation, diabetes mellitus, severe asthma, ethnicity, NHS England, cohort studies
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Aging, Asthma, Diabetes Mellitus, Female, Humans, Hypertension, Male, Middle Aged, Pneumonia, Viral, Sex Characteristics, Smoking, State Medicine, Cohort Studies, Proportional Hazards Models, Age Distribution, Coronavirus Infections, Risk Assessment, Black People, Asian People, Young Adult, Pandemics
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