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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.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Ip, Samantha 
Cooper, Jennifer A 
Bolton, Thomas 

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.

Description

Keywords

COVID-19, electronic health records, myocardial infarction, pulmonary embolism, stroke, thrombosis, venous thrombosis, Adult, COVID-19, COVID-19 Vaccines, Cohort Studies, Humans, SARS-CoV-2, Thrombosis, Vascular Diseases, Venous Thromboembolism, Venous Thrombosis, Wales

Journal Title

Circulation

Conference Name

Journal ISSN

0009-7322
1524-4539

Volume Title

146

Publisher

Ovid Technologies (Wolters Kluwer Health)
Sponsorship
MRC (via University College London (UCL)) (MC_PC_20059)
British Heart Foundation (None)
British Heart Foundation (CH/12/2/29428)
British Heart Foundation (RG/18/13/33946)
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 BHF Data Science Centre led by HDR UK (BHF grant number SP/19/3/34678), and 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). This work uses data provided by patients and collected by the NHS as part of their care and support. We would also like to acknowledge all data providers who make anonymised data available for research. This work was supported by the Con-COV team funded by the Medical Research Council (grant number: MR/V028367/1). This work was supported by Health Data Research UK, which receives its funding from HDR 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 (BHF) and the Wellcome Trust. This work was supported by core funding from the: British Heart Foundation (BHF; RG/13/13/30194; RG/18/13/33946), BHF Cambridge CRE (RE/13/6/30180) and NIHR Cambridge Biomedical Research Centre (BRC-1215-20014) [*]. This work was supported by the ADR Wales programme of work. The ADR Wales programme of work 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 (WISERD) at Cardiff University and specialist teams within the Welsh Government to develop new evidence which supports Prosperity for All by using the SAIL Databank at Swansea University, to link and analyse anonymised 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). This work was supported by the Wales COVID-19 Evidence Centre, funded by Health and Care Research Wales. SI was funded by a BHF-Turing Cardiovascular Data Science Award (BCDSA\100005) and is funded by a University College London FB Cancer Research UK Award (C18081/A31373). RK, JAC and JACS were supported by the NIHR Bristol Biomedical Research Centre. RK, VW GDS were supported by the MRC Integrative Epidemiology Unit at the University of Bristol. RK was supported by NIHR ARC West. RD and JACS were supported by Health Data Research UK. SK is funded by the NIHR Blood and Transplant Research Unit in Donor Health and Genomics (NIHR BTRU-2014-10024). TM was funded by the NIHR Blood and Transplant Research Unit in Donor Health and Genomics (NIHR BTRU-2014-10024). AMW is part of the BigData@Heart Consortium, funded by the Innovative Medicines Initiative-2 Joint Undertaking under grant agreement No 116074 and was supported by the BHF-Turing Cardiovascular Data Science Award (BCDSA\100005). WW is supported by the Chief Scientist’s Office (CAF/01/17). CS, CS, MB AW and WW are supported by Stroke Association (SA CV 20\100018).
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