@article{d0251ecb36304432945e422e1f6ffc4a,
title = "Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort",
abstract = "OBJECTIVE: To evaluate antithrombotic (AT) use in individuals with atrial fibrillation (AF) and at high risk of stroke (CHA2DS2-VASc score ≥2) and investigate whether pre-existing AT use may improve COVID-19 outcomes.METHODS: Individuals with AF and CHA2DS2-VASc score ≥2 on 1 January 2020 were identified using electronic health records for 56 million people in England and were followed up until 1 May 2021. Factors associated with pre-existing AT use were analysed using logistic regression. Differences in COVID-19-related hospitalisation and death were analysed using logistic and Cox regression in individuals with pre-existing AT use versus no AT use, anticoagulants (AC) versus antiplatelets (AP), and direct oral anticoagulants (DOACs) versus warfarin.RESULTS: From 972 971 individuals with AF (age 79 (±9.3), female 46.2%) and CHA2DS2-VASc score ≥2, 88.0% (n=856 336) had pre-existing AT use, 3.8% (n=37 418) had a COVID-19 hospitalisation and 2.2% (n=21 116) died, followed up to 1 May 2021. Factors associated with no AT use included comorbidities that may contraindicate AT use (liver disease and history of falls) and demographics (socioeconomic status and ethnicity). Pre-existing AT use was associated with lower odds of death (OR=0.92, 95% CI 0.87 to 0.96), but higher odds of hospitalisation (OR=1.20, 95% CI 1.15 to 1.26). AC versus AP was associated with lower odds of death (OR=0.93, 95% CI 0.87 to 0.98) and higher hospitalisation (OR=1.17, 95% CI 1.11 to 1.24). For DOACs versus warfarin, lower odds were observed for hospitalisation (OR=0.86, 95% CI 0.82 to 0.89) but not for death (OR=1.00, 95% CI 0.95 to 1.05).CONCLUSIONS: Pre-existing AT use may be associated with lower odds of COVID-19 death and, while not evidence of causality, provides further incentive to improve AT coverage for eligible individuals with AF.",
keywords = "Aged, Anticoagulants/adverse effects, Atrial Fibrillation/complications, COVID-19/epidemiology, Female, Fibrinolytic Agents, Humans, Risk Assessment, Risk Factors, Stroke/etiology, Warfarin",
author = "{CVD-COVID-UK consortium} and Alex Handy and Amitava Banerjee and Wood, {Angela M} and Dale, {Caroline E} and Sudlow, {Cathie L M} and Christopher Tomlinson and Daniel Bean and Thygesen, {Johan H} and Mizani, {Mehrdad A} and Michail Katsoulis and Rohan Takhar and Sam Hollings and Spiros Denaxas and Venexia Walker and Richard Dobson and Reecha Sofat",
note = "Funding Information: The British Heart Foundation Data Science Centre (grant no: SP/19/3/34678, awarded to Health Data Research (HDR) UK) funded the co-development (with NHS Digital) of the Trusted Research Environment, provision of linked data sets, data access, user software licences, computational usage, and data management and wrangling support, with additional contributions from the HDR UK dData and cConnectivity component of the UK Governments{\textquoteright} cChief sScientific aAdviser{\textquoteright}s nNational cCore sStudies programme to coordinate national COVID-19 priority research. Consortium partner organisations funded the time of contributing data analysts, biostatisticians, epidemiologists and clinicians.AH is supported by research funding from the HDR UK Text Analytics Implementation Project. AB is supported by research funding from the National Institute for Health Research (NIHR), British Medical Association, AstraZeneca, and UK Research and Innovation. AMW is supported by the BHF-Turing Cardiovascular Data Science award (BCDSA\100005) and by core funding from UK MRC (MR/L003120/1), BHF (RG/13/13/30194; RG/18/13/33946) and NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). CT is supported by a UCL UKRI Centre for Doctoral Training in AI-enabled Healthcare studentship (EP/S021612/1), MRC Clinical Top-Up and a studentship from the NIHR Biomedical Research Centre at University College London Hospitals NHS Trust. DB holds a UK Research and Innovation (UKRI) Fellowship as part of Health Data Research UK (HDRUK; MR/S00310X/1). MAM is supported by research funding from AstraZeneca. MK is funded by the British Heart Foundation (grant: FS/18/5/33319). RD is supported by (1) NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King{\textquoteright}s College London, London, UK; (2) Health Data Research UK, which is 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 Wellcome Trust; (3) the BigData@Heart Consortium, funded by the Innovative Medicines Initiative-2 Joint Undertaking (grant agreement no: 116074; this Joint Undertaking receives support from the European Union{\textquoteright}s Horizon 2020 research and innovation programme and EFPIA and is chaired by DE Grobbee and SD Anker, partnering with 20 academic and industry partners and ESC); (4) the National Institute for Health Research University College London Hospitals Biomedical Research Centre; (5) the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King{\textquoteright}s College London; (6) the UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare; and (7) the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King{\textquoteright}s College Hospital NHS Foundation Trust. SD is supported by: (1) Health Data Research UK London, which receives its funding from HDR UK funded by the UK MRC, EPSRC, ESRC, 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), BHF, and Wellcome Trust; (2) The NIHR Biomedical Research Centre at University College London Hospital NHS Trust; (3) The Alan Turing Institute (EP/N510129/1); (4) The British Heart Foundation Accelerator Award (ref AA/18/6/24223); (5) The BigData@Heart Consortium, funded by the Innovative Medicines Initiative-2 Joint Undertaking under grant agreement (ref 116074); (6) The British Heart Foundation Data Science Centre (ref SP/19/3/34678); (7) The UKRI/NIHR funded Multimorbidity Mechanism and Therapeutics Research Collaborative (MR/V033867/1); (8) 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), (9) 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), and (10) The CONVALESCENCE study of long COVID, which is funded by NIHR/UKRI.AB, AMW, RD and SD are part of the BigData@Heart Consortium, funded by the Innovative Medicines Initiative-2 Joint Undertaking (grant agreement no: 116074). Publisher Copyright: {\textcopyright} Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.",
year = "2022",
month = mar,
day = "10",
doi = "10.1136/heartjnl-2021-320325",
language = "English",
volume = "108",
pages = "923--931",
journal = "Heart",
issn = "1355-6037",
publisher = "BMJ Publishing Group",
number = "12",
}