COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records.

Show simple item record

dc.contributor.author Thygesen, Johan H
dc.contributor.author Tomlinson, Christopher
dc.contributor.author Hollings, Sam
dc.contributor.author Mizani, Mehrdad A
dc.contributor.author Handy, Alex
dc.contributor.author Akbari, Ashley
dc.contributor.author Banerjee, Amitava
dc.contributor.author Cooper, Jennifer
dc.contributor.author Lai, Alvina G
dc.contributor.author Li, Kezhi
dc.contributor.author Mateen, Bilal A
dc.contributor.author Sattar, Naveed
dc.contributor.author Sofat, Reecha
dc.contributor.author Torralbo, Ana
dc.contributor.author Wu, Honghan
dc.contributor.author Wood, Angela
dc.contributor.author Sterne, Jonathan AC
dc.contributor.author Pagel, Christina
dc.contributor.author Whiteley, William N
dc.contributor.author Sudlow, Cathie
dc.contributor.author Hemingway, Harry
dc.contributor.author Denaxas, Spiros
dc.contributor.author Longitudinal Health and Wellbeing COVID-19 National Core Study and the CVD-COVID-UK/COVID-IMPACT Consortium
dc.coverage.spatial England
dc.date.accessioned 2022-08-15T03:36:18Z
dc.date.available 2022-08-15T03:36:18Z
dc.date.issued 2022-07
dc.identifier.citation (2022). Lancet Digital Health, 4(7), e542-e557.
dc.identifier.issn 2589-7500
dc.identifier.uri https://hdl.handle.net/2292/60795
dc.description.abstract <h4>Background</h4>Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework.<h4>Methods</h4>In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status.<h4>Findings</h4>Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1.<h4>Interpretation</h4>Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources.<h4>Funding</h4>British Heart Foundation Data Science Centre, led by Health Data Research UK.
dc.format.medium Print-Electronic
dc.language eng
dc.publisher Elsevier
dc.relation.ispartofseries The Lancet. Digital health
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher.
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject Longitudinal Health and Wellbeing COVID-19 National Core Study and the CVD-COVID-UK/COVID-IMPACT Consortium
dc.subject Humans
dc.subject Cohort Studies
dc.subject State Medicine
dc.subject England
dc.subject Electronic Health Records
dc.subject COVID-19
dc.subject SARS-CoV-2
dc.subject COVID-19 Testing
dc.subject Clinical Research
dc.subject Health Services
dc.subject Patient Safety
dc.subject 2 Aetiology
dc.subject 2.4 Surveillance and distribution
dc.subject Infection
dc.subject 3 Good Health and Well Being
dc.title COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records.
dc.type Journal Article
dc.identifier.doi 10.1016/s2589-7500(22)00091-7
pubs.issue 7
pubs.begin-page e542
pubs.volume 4
dc.date.updated 2022-07-14T20:35:08Z
dc.rights.holder Copyright: The authors en
dc.identifier.pmid 35690576 (pubmed)
pubs.author-url https://www.ncbi.nlm.nih.gov/pubmed/35690576
pubs.end-page e557
pubs.publication-status Published
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.subtype Research Support, Non-U.S. Gov't
pubs.subtype research-article
pubs.subtype Journal Article
pubs.elements-id 911079
pubs.org-id Medical and Health Sciences
pubs.org-id Population Health
dc.identifier.eissn 2589-7500
dc.identifier.pii S2589-7500(22)00091-7
pubs.record-created-at-source-date 2022-07-15
pubs.online-publication-date 2022-07


Files in this item

Find Full text

This item appears in the following Collection(s)

Show simple item record

Share

Search ResearchSpace


Browse

Statistics