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Association of COVID-19 With Major Arterial and Venous Thrombotic Diseases: A Population-Wide Cohort Study of 48 Million Adults in England and Wales
Circulation, Volume: 146, Issue: 12, Pages: 892 - 906
Swansea University Authors:
Ashley Akbari , Hoda Abbasizanjani
, Fatemeh Torabi
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© 2022 The Authors. This is an open access article under the terms of the Creative Commons Attribution License
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DOI (Published version): 10.1161/circulationaha.122.060785
Abstract
Background:Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a prothrombotic state, but long-term effects of COVID-19 on incidence of vascular diseases are unclear.Methods:We studied vascular diseases after COVID-19 diagnosis in population-wide anonymized linked Eng...
Published in: | Circulation |
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ISSN: | 0009-7322 1524-4539 |
Published: |
Ovid Technologies (Wolters Kluwer Health)
2022
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Online Access: |
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URI: | https://cronfa.swan.ac.uk/Record/cronfa61291 |
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Abstract: |
Background:Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a prothrombotic state, but long-term effects of COVID-19 on incidence of vascular diseases are unclear.Methods:We studied vascular diseases after COVID-19 diagnosis in population-wide anonymized linked English and Welsh electronic health records from January 1 to December 7, 2020. We estimated adjusted hazard ratios comparing the incidence of arterial thromboses and venous thromboembolic events (VTEs) after diagnosis of COVID-19 with the incidence in people without a COVID-19 diagnosis. We conducted subgroup analyses by COVID-19 severity, demographic characteristics, and previous history.Results:Among 48 million adults, 125 985 were hospitalized and 1 319 789 were not hospitalized within 28 days of COVID-19 diagnosis. In England, there were 260 279 first arterial thromboses and 59 421 first VTEs during 41.6 million person-years of follow-up. Adjusted hazard ratios for first arterial thrombosis after COVID-19 diagnosis compared with no COVID-19 diagnosis declined from 21.7 (95% CI, 21.0–22.4) in week 1 after COVID-19 diagnosis to 1.34 (95% CI, 1.21–1.48) during weeks 27 to 49. Adjusted hazard ratios for first VTE after COVID-19 diagnosis declined from 33.2 (95% CI, 31.3–35.2) in week 1 to 1.80 (95% CI, 1.50–2.17) during weeks 27 to 49. Adjusted hazard ratios were higher, for longer after diagnosis, after hospitalized versus nonhospitalized COVID-19, among Black or Asian versus White people, and among people without versus with a previous event. The estimated whole-population increases in risk of arterial thromboses and VTEs 49 weeks after COVID-19 diagnosis were 0.5% and 0.25%, respectively, corresponding to 7200 and 3500 additional events, respectively, after 1.4 million COVID-19 diagnoses.Conclusions:High relative incidence of vascular events soon after COVID-19 diagnosis declines more rapidly for arterial thromboses than VTEs. However, incidence remains elevated up to 49 weeks after COVID-19 diagnosis. These results support policies to prevent severe COVID-19 by means of COVID-19 vaccines, early review after discharge, risk factor control, and use of secondary preventive agents in high-risk patients. |
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Keywords: |
COVID-19; electronic health records; myocardial infarction; pulmonary embolism; stroke; thrombosis; venous thrombosis |
College: |
Faculty of Medicine, Health and Life Sciences |
Funders: |
This work was funded by the Longitudinal Health and Wellbeing COVID-19 National Core Study, which was established by the UK Chief Scientific Officer in
October 2020 and funded by UK Research and Innovation (grant references
MC_PC_20030 and MC_PC_20059); by the British Heart Foundation as part of
the British Heart Foundation Data Science Center led by Health Data Research
UK (British Heart Foundation grant number SP/19/3/34678); by the Data and
Connectivity National Core Study led by Health Data Research UK in partnership
with the Office for National Statistics and funded by UK Research and Innovation
(grant reference MC_PC_20058); by the CONVALESCENCE study of long COVID-19 funded by National Institute for Health and Care Research (NIHR)/UK
Research and Innovation; by the Con-COV team funded by the Medical Research
Council (grant number MR/V028367/1); by Health Data Research UK, which
receives its funding from Health Data Research UK Ltd (HDR-9006) funded by
the UK Medical Research Council, Engineering and Physical Sciences Research
Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and
Social Care Directorates, Health and Social Care Research and Development
Division (Welsh Government), Public Health Agency (Northern Ireland), British
Heart Foundation, and the Wellcome Trust; by core funding from the British Heart
Foundation (RG/13/13/30194; RG/18/13/33946), British Heart Foundation
Cambridge CRE (RE/13/6/30180), and NIHR Cambridge Biomedical Research Center (BRC-1215-20014); by the ADR Wales program of work, which
is aligned to the priority themes as identified in the Welsh Government’s national
strategy: Prosperity for All (ADR Wales brings together data science experts at
Swansea University Medical School, staff from the Wales Institute of Social and
Economic Research, Data and Methods at Cardiff University, and specialist teams
within the Welsh Government to develop new evidence that supports Prosperity
for All by using the SAIL Databank at Swansea University to link and analyze anonymized data; ADR Wales is part of the Economic and Social Research Council
[part of UK Research and Innovation] funded ADR UK [grant ES/S007393/1]);
by the Wales COVID-19 Evidence Center, funded by Health and Care Research
Wales; and by the BigData@Heart Consortium, funded by the Innovative Medicines Initiative-2 Joint Undertaking under grant agreement 116074. Dr Ip was
funded by a British Heart Foundation–Turing Cardiovascular Data Science 419
Award (BCDSA/100005) and is funded by the International Alliance for Cancer
Early Detection, a partnership among Cancer Research UK C18081/A31373,
Canary Center at Stanford University, the University of Cambridge, OHSU Knight
Cancer Institute, University College London, and the University of Manchester. R.
Knight and Drs Cooper and Sterne were supported by the NIHR Bristol Biomedical Research Center. R. Knight and Drs Walker and Davey Smith were supported
by the Medical Research Council Integrative Epidemiology Unit at the University
of Bristol (MC_UU_00011/1). R. Knight was supported by NIHR ARC West. Drs
Denholm and Sterne were supported by Health Data Research UK. S. Keene is
funded by the NIHR Blood and Transplant Research Unit in Donor Health and
Genomics (NIHR BTRU-2014-10024). X. Jiang was funded by the Health Data
Research UK–Turing Wellcome PhD Programme in Health Data Science. Dr
Wood was supported by the British Heart Foundation–Turing Cardiovascular
Data Science Award (BCDSA/100005). Dr Whiteley is supported by the Chief
Scientist’s Office (CAF/01/17). Drs Sudlow, Smith, Barber, Wood, and Whiteley
are supported by the Stroke Association (SA CV 20/100018). C. Tomlinson is
supported by a University College London UK Research and Innovation Center
for Doctoral Training in AI-Enabled Healthcare studentship (EP/S021612/1),
Medical Research Council Clinical Top-Up, and a studentship from the NIHR Biomedical Research Center at University College London Hospital National Health
Service Trust. The views expressed are those of the authors and not necessarily
those of the NIHR or the Department of Health and Social Care. |
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12 |
Start Page: |
892 |
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