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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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BackgroundObservational study of haloperidol in hospitalized patients with COVID-19
Hoertel, N., Rico, M. S., Vernet, R., Jannot, A., Neuraz, A., Blanco, C., Lemogne, C., Airagnes, G., Paris, N., Daniel, C., et al. (2021) · PLoS ONE · doi:10.1371/journal.pone.0247122 · Cited by 57
Covid-19 and rural landscape: The case of Italy
Agnoletti, M., Manganelli, S., & Piras, F. (2020) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2020.103955 · Cited by 53
SARS-CoV-2 Infection and the Liver
Morgan, K., Samuel, K., Vandeputte, M., Hayes, P. C., & Plevris, J. N. (2020) · Pathogens · doi:10.3390/pathogens9060430 · Cited by 43
“A very recent study conducted in the UK on more than 17 million people has identified pre-existing liver disease as an independent risk factor of death in SARS-CoV-2 infections [42].”
BackgroundAsymptomatic SARS-CoV-2 infection
Ooi, E., & Low, J. (2020) · Lancet. Infectious Diseases (Print) · doi:10.1016/s1473-3099(20)30460-6 · Cited by 47
Marra, F., Smolders, E. J., El‐Sherif, O., Boyle, A., Davidson, K., Sommerville, A., Marzolini, C., Siccardi, M., Burger, D., Gibbons, S., et al. (2020) · Drugs in R&D · doi:10.1007/s40268-020-00333-0 · Cited by 51
“Additionally, in a large population study of hospitalised patients with COVID-19 in the UK, pre-existing liver disease was associated with an increased age-adjusted mortality [12].”
BackgroundSevere COVID-19 in Patients with B Cell Alymphocytosis and Response to Convalescent Plasma Therapy
London, J., Boutboul, D., Lacombe, K., Pirenne, F., Heym, B., Zeller, V., Baudet, A., Ouedrani, A., & BEREZNE, A. (2020) · Journal of Clinical Immunology · doi:10.1007/s10875-020-00904-5 · Cited by 37
Les inégalités sociales au temps du COVID-19
Bajos, N., Warszawski, J., Pailhé, A., Counil, É., Jusot, F., Spire, A., Martin, C., Meyer, L., Sireyjol, A., Franck, J.-E., et al. (2020) · Questions de santé publique · doi:10.1051/qsp/2020040 · Cited by 51
“Ces mêmes groupes sociaux connaissent en outre des prévalences plus élevées de pathologies associées au risque de développer une forme grave de la maladie [14].”
BackgroundZazzara, M. B., Penfold, R., Roberts, A. L., Lee, K. A., Dooley, H. C., Sudre, C. H., Welch, C., Bowyer, R. C. E., Visconti, A., Mangino, M., et al. (2020) · Age and Ageing · doi:10.1093/ageing/afaa223 · Cited by 109
“greater number of chronic diseases[6] and immunosenescence[7,8].”
de Lusignan, S., Joy, M., Oke, J. L., McGagh, D., Nicholson, B. D., Sheppard, J. P., Akinyemi, O., Amirthalingam, G., Brown, K. E., Byford, R. C., et al. (2020) · Journal of Infection · doi:10.1016/j.jinf.2020.08.037 · Cited by 37
Mason, K., McHale, P., Pennington, A., Maudsley, G., Day, J., & Barr, B. (2021) · Frontiers in Public Health · doi:10.3389/fpubh.2021.584182 · Cited by 43
Coccidioidomycosis and COVID-19 Co-Infection, United States, 2020
Heaney, A. K., Head, J. R., Broen, K., Click, K., Taylor, J. W., Balmes, J. R., Zelner, J., & Remais, J. V. (2021) · Emerging infectious diseases · doi:10.3201/eid2705.204661 · Cited by 53
The need for improved collection and coding of ethnicity in health research
Khunti, K. K., Routen, A. C., Banerjee, A., & Pareek, M. (2020) · Journal of Public Health · doi:10.1093/pubmed/fdaa198 · Cited by 47
Ensuring that COVID-19 research is inclusive: guidance from the NIHR INCLUDE project
Witham, M. D., Anderson, E. M., Carroll, C., Dark, P. M., Down, K., Hall, A. S., Knee, J., Maher, E. R., Maier, R. H., Mountain, G. A., et al. (2020) · BMJ Open · doi:10.1136/bmjopen-2020-043634 · Cited by 48
Mathur, R., Rentsch, C., Morton, C., et al. (2020) · medRxiv · doi:10.1101/2020.09.22.20198754 · Cited by 44
Self-citationInfections and diabetes: Risks and mitigation with reference to India
Ranjit Unnikrishnan, I., & Misra, A. (2020) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2020.09.022 · Cited by 55
Assessment of workers’ personal vulnerability to covid-19 using ‘covid-age’
Coggon, D., Croft, P., Cullinan, P., et al. (2020) · medRxiv · doi:10.1101/2020.05.21.20108969 · Cited by 44
“Produced by the OpenSAFELY (OS) collaborative, it presented first results from a cohort study of more than 17 million adults registered with English general practices and followed between 1 February and 25 April 2020 [6].”
MethodEarly Evidence of Disparities in COVID-19 Testing in US Cities
Bilal, U., Barber, S., Tabb, L., et al. (2020) · medRxiv · doi:10.1101/2020.05.01.20087833 · Cited by 44
Perceived Social Norm and Behavior Quickly Adjusted to Legal Changes During the COVID-19 Pandemic
Casoria, F., Galeotti, F., & Villeval, M. C. (2020) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2021.07.030 · Cited by 49
Novak, N., & Cabanillas, B. (2020) · Immunology · doi:10.1111/imm.13240 · Cited by 47
How evolutionary behavioural sciences can help us understand behaviour in a pandemic
Arnot, M., Brandl, E., Campbell, O. L. K., Chen, Y., Du, J., Dyble, M., Emmott, E. H., Ge, E., Kretschmer, L., Mace, R. H., et al. (2020) · Evolution Medicine and Public Health · doi:10.1093/emph/eoaa038 · Cited by 49
“Younger individuals of reproductive age therefore face different trade-offs from older individuals of post-reproductive age even before considering age-specific differences in mortality risk observed due to COVID-19 [6].”
BackgroundTalamonti, M., Galluzzo, M., Chiricozzi, A., et al. (2020) · Expert Opinion on Biological Therapy · doi:10.1080/14712598.2021.1853698 · Cited by 42
“35) hazard ratio for inhospital COVID-19 death, independent of other risk factors [4].”
BackgroundCOVID-19–related Mortality During the First 60 Days After Kidney Transplantation
Pascual, J., Melilli, E., Jiménez-Martín, C., González‐Monte, E., Zárraga, S., Gutiérrez-Dalmau, Á., López‐Jiménez, V., Juega, J., Muñoz-Cepeda, M. Á., Lorenzo, I., et al. (2020) · European Urology · doi:10.1016/j.eururo.2020.06.036 · Cited by 48
Who is most likely to be infected with SARS-CoV-2?
Jordan, R. E., & Adab, P. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30395-9 · Cited by 47
Antibiotic resistance during and beyond COVID-19
Livermore, D. M. (2021) · JAC-Antimicrobial Resistance · doi:10.1093/jacamr/dlab052 · Cited by 45
Mareev, V. Y., Orlova, Y. A., Павликова, Е. П., Мацкеплишвили, С. Т., Krasnova, T. N., Малахов, П. С., Samokhodskaya, L. M., Mershina, E. A., Sinitsyn, V. E., Mareev, Y. V., et al. (2020) · Kardiologiia · doi:10.18087/cardio.2020.6.n1226 · Cited by 54
“The maximum risk of death is observed in the subgroup of patients over 80 years old, in which this risk is 6 times higher than in patients aged 65 [13].”
BackgroundSARS‐CoV‐2 infection in patients with a normal or abnormal liver
Cabibbo, G., Rizzo, G. E. M., Stornello, C., & Craxı̀, A. (2020) · Journal of Viral Hepatitis · doi:10.1111/jvh.13440 · Cited by 44
Socio-demographic risk factors of COVID-19 deaths in Sweden: A nationwide register study
Drefahl, S., Wallace, M., Mussino, E., et al. (2020) · doi:10.17045/sthlmuni.12420347.v4 · Cited by 40
“These initial findings suggest that men (2–6), the elderly (2–11), racial and ethnic minorities (4, 6, 7, 12), and people occupying lower socioeconomic positions (4, 6), are more prone to developing severe COVID-19, or dying from it.”
BackgroundJain, V., Schwarz, L., & Lorgelly, P. (2021) · medRxiv · doi:10.3390/ijerph18073483 · Cited by 39
Kidney transplantation and COVID-19 renal and patient prognosis
Toapanta, N., Torres, I. B., Sellarés, J., Chamoun, B., Serón, D., & Moreso, F. (2021) · Clinical Kidney Journal · doi:10.1093/ckj/sfab030 · Cited by 46
Mortality associated with cardiovascular disease in patients with COVID-19
Cordero, A., García-Gallego, C. S., Bertomeu‐González, V., Fácila, L., Rodríguez‐Mañero, M., Escribano, D., Castellano, J. M., Zuazola, P., Núñez, J. E., Badimón, J. J., et al. (2020) · REC CardioClinics · doi:10.1016/j.rccl.2020.10.005 · Cited by 37
Sainsbury, C. A. R., Wang, J., Gokhale, K. M., Acosta, D., Dhalla, S., Byne, N., Chandan, J. S., Anand, A., Cooper, J. M., Okoth, K., et al. (2020) · Diabetes Obesity and Metabolism · doi:10.1111/dom.14203 · Cited by 43
Justice, J. N., Gubbi, S., Kulkarni, A. S., Bartley, J. M., Kuchel, G. A., & Barzilai, N. (2020) · GeroScience · doi:10.1007/s11357-020-00261-6 · Cited by 53
Pulling at the heart: COVID-19, race/ethnicity and ongoing disparities
Chin-Hong, P., Alexander, K., Haynes, N., et al. (2020) · Nature Reviews Cardiology · doi:10.1038/s41569-020-0416-6 · Cited by 38
Observational Study of Chlorpromazine in Hospitalized Patients with COVID-19
Hoertel, N., Rico, M. S., Vernet, R., Jannot, A., Neuraz, A., Blanco, C., Lemogne, C., Airagnes, G., Paris, N., Daniel, C., et al. (2021) · Clinical Drug Investigation · doi:10.1007/s40261-021-01001-0 · Cited by 44
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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