OpenSAFELY: factors associated with COVID-19 death in 17 million patients. Williamson, E. J, 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. Y., Grieve, R., Harrison, D., Forbes, H., Schultze, A., Croker, R., Parry, J., Hester, F., Harper, S., Perera, R., Evans, S. J., Smeeth, L., & Goldacre, B. Nature, 584(7821):430, August, 2020. Publisher: Europe PMC Funders![OpenSAFELY: factors associated with COVID-19 death in 17 million patients [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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.
@article{williamson_opensafely_2020,
title = {{OpenSAFELY}: factors associated with {COVID}-19 death in 17 million patients},
volume = {584},
url = {/pmc/articles/PMC7611074/},
doi = {10.1038/S41586-020-2521-4},
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.},
number = {7821},
urldate = {2021-08-17},
journal = {Nature},
author = {Williamson, Elizabeth J and Walker, Alex J and Bhaskaran, Krishnan and Bacon, Seb and Bates, Chris and Morton, Caroline E and Curtis, Helen J and Mehrkar, Amir and Evans, David and Inglesby, Peter and Cockburn, Jonathan and McDonald, Helen I and MacKenna, Brian and Tomlinson, Laurie and Douglas, Ian J and Rentsch, Christopher T and Mathur, Rohini and Wong, Angel YS and Grieve, Richard and Harrison, David and Forbes, Harriet and Schultze, Anna and Croker, Richard and Parry, John and Hester, Frank and Harper, Sam and Perera, Rafael and Evans, Stephen JW and Smeeth, Liam and Goldacre, Ben},
month = aug,
year = {2020},
pmid = {32640463},
note = {Publisher: Europe PMC Funders},
keywords = {COVID-19, death, deprivation, ethnicity, informatics, risk factors},
pages = {430},
}
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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. 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