Overall and cause-specific hospitalisation and death after COVID-19 hospitalisation in England: A cohort study using linked primary care, secondary care, and death registration data in the OpenSAFELY platform

Krishnan Bhaskaran, Christopher T Rentsch, George Hickman, William J Hulme, Anna Schultze, Helen J Curtis, Kevin Wing, Charlotte Warren-Gash, Laurie Tomlinson, Chris J Bates, Rohini Mathur, Brian MacKenna, Viyaasan Mahalingasivam, Angel Wong, Alex J Walker, Caroline E Morton, Daniel Grint, Amir Mehrkar, Rosalind M Eggo, Peter InglesbyIan J Douglas, Helen I McDonald, Jonathan Cockburn, Elizabeth J Williamson, David Evans, John Parry, Frank Hester, Sam Harper, Stephen Jw Evans, Sebastian Bacon, Liam Smeeth, Ben Goldacre

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Background There is concern about medium to long-term adverse outcomes following acute Coronavirus Disease 2019 (COVIDAU : PleasenotethatCOVID 19hasbeendefinedasCoronavirusDisease2019atitsfirstmentionintheAbstractandinthemaintext:-19), but little relevant evidence exists.We aimed to investigate whether risks of hospital admission and death, overall and by specific cause, are raised following discharge from a COVID-19 hospitalisation. Methods and findings With the approval of NHS-England, we conducted a cohort study, using linked primary care and hospital data in OpenSAFELY to compare risks of hospital admission and death, overall and by specific cause, between people discharged from COVID-19 hospitalisation (February to December 2020) and surviving at least 1 week, and (i) demographically matched controls from the 2019 general population; and (ii) people discharged from influenza hospitalisation in 2017 to 2019. We used Cox regression adjusted for age, sex, ethnicity, obesity, smoking status, deprivation, and comorbidities considered potential risk factors for severe COVID-19 outcomes. We included 24,673 postdischarge COVID-19 patients, 123,362 general population controls, and 16,058 influenza controls, followed for ?315 days. COVID-19 patients had median age of 66 years, 13,733 (56%) were male, and 19,061 (77%) were of white ethnicity. Overall risk of hospitalisation or death (30,968 events) was higher in the COVID-19 group than general population controls (fully adjusted hazard ratio [aHR] 2.22, 2.14 to 2.30, p0.001) but slightly lower than the influenza group (aHR 0.95, 0.91 to 0.98, p = 0.004). All-cause mortality (7,439 events) was highest in the COVID-19 group (aHR 4.82, 4.48 to 5.19 versus general population controls [p0.001] and 1.74, 1.61 to 1.88 versus influenza controls [p0.001]). Risks for cause-specific outcomes were higher in COVID-19 survivors than in general population controls and largely similar or lower in COVID-19 compared with influenza patients. However, COVID-19 patients were more likely than influenza patients to be readmitted or die due to their initial infection or other lower respiratory tract infection (aHR 1.37, 1.22 to 1.54, p0.001) and to experience mental health or cognitive-related admission or death (aHR 1.37, 1.02 to 1.84, p = 0.039); in particular, COVID-19 survivors with preexisting dementia had higher risk of dementia hospitalisation or death (age- and sex-adjusted HR 2.47, 1.37 to 4.44, p = 0.002). Limitations of our study were that reasons for hospitalisation or death may have been misclassified in some cases due to inconsistent use of codes, and we did not have data to distinguish COVID-19 variants. Conclusions In this study, we observed that people discharged from a COVID-19 hospital admission had markedly higher risks for rehospitalisation and death than the general population, suggesting a substantial extra burden on healthcare. Most risks were similar to those observed after influenza hospitalisations, but COVID-19 patients had higher risks of all-cause mortality, readmission or death due to the initial infection, and dementia death, highlighting the importance of postdischarge monitoring.

Original languageEnglish
Article numbere1003871
Pages (from-to)e1003871
JournalPLoS Medicine
Issue number1
Early online date25 Jan 2022
Publication statusPublished - 25 Jan 2022
Externally publishedYes

Bibliographical note

Funding Information:
This work was jointly funded by UKRI, NIHR and Asthma UK-BLF [COV0076; MR/ V015737/] and the Longitudinal Health and Wellbeing strand of the National Core Studies programme. The OpenSAFELY data science platform is funded by the Wellcome Trust. TPP provided technical expertise and infrastructure within their data centre pro bono in the context of a national emergency. KB holds a Senior Research Fellowship from Wellcome (220283/Z/20/Z). RME is funded by HDR UK (grant: MR/S003975/1) and MRC (grant: MC_PC 19065). RM holds a Sir Henry Wellcome fellowship funded by Wellcome. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Funding Information:
Funding:ThisworkwasjointlyfundedbyUKRI, NIHRandAsthmaUK-BLF[COV0076;MR/ V015737/]andtheLongitudinalHealthand WellbeingstrandoftheNationalCoreStudies programme.TheOpenSAFELYdatascience platformisfundedbytheWellcomeTrust.TPP providedtechnicalexpertiseandinfrastructure withintheirdatacentreprobonointhecontextofa nationalemergency.KBholdsaSeniorResearch FellowshipfromWellcome(220283/Z/20/Z).RME isfundedbyHDRUK(grant:MR/S003975/1)and MRC(grant:MC_PC19065).RMholdsaSirHenry WellcomefellowshipfundedbyWellcome.The fundershadnoroleinstudydesign,datacollection andanalysis,decisiontopublish,orpreparationof themanuscript.

Publisher Copyright:
© 2022 Public Library of Science. All rights reserved.


  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • COVID-19/complications
  • Case-Control Studies
  • Cause of Death
  • England/epidemiology
  • Female
  • Follow-Up Studies
  • Hospitalization/statistics & numerical data
  • Humans
  • Information Storage and Retrieval
  • Male
  • Middle Aged
  • Primary Health Care
  • Proportional Hazards Models
  • Registries
  • Risk Factors
  • Secondary Care
  • Young Adult


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