Patient characteristics associated with clinically coded long COVID: an OpenSAFELY study using electronic health records
Patient characteristics associated with clinically coded long COVID: an OpenSAFELY study using electronic health records
ABSTRACT Despite reports of post-COVID-19 syndromes (long COVID) are rising, clinically coded long COVID cases are incomplete in electronic health records. It is unclear how patient characteristics may be associated with clinically coded long COVID. With the approval of NHS England, we undertook a cohort study using electronic health records within the OpenSAFELY-TPP platform in England, to study patient characteristics associated with clinically coded long COVID from 29 January 2020 to 31 March 2022. We estimated age-sex adjusted hazard ratios and fully adjusted hazard ratios for coded long COVID. Patient characteristics included demographic factors, and health behavioural and clinical factors. Among 17,986,419 adults, 36,886 (0.21%) were clinically coded with long COVID. Patient characteristics associated with coded long COVID included female sex, younger age (under 60 years), obesity, living in less deprived areas, ever smoking, greater consultation frequency, and history of diagnosed asthma, mental health conditions, pre-pandemic post-viral fatigue, or psoriasis. The strength of these associations was attenuated following two-dose vaccination compared to before vaccination. The incidence of coded long COVID was higher after hospitalised than non-hospitalised COVID-19. These results should be interpreted with caution given that long COVID was likely under-recorded in electronic health records.
Knight Rochelle、Walker Venexia、Riley Stephanie、Silverwood Richard J、Wood Angela M、Steves Claire、Sterne Jonathan AC、Cezard Genevieve、Fisher Louis、Denholm Rachel、Goldacre Ben、Mehrkar Amir、Greaves Felix、Walker Alex、Taylor Kurt、Wei Yinghui、Denaxas Spiros、Bacon Sebastian、Davy Simon、Williams Dylan M、Macleod John、Horne Elsie MF、Willans Robert、Chaturvedi Nish、Sheikh Aziz
Population Health Sciences, Bristol Medical School, University of Bristol||NIHR Bristol Biomedical Research Centre||MRC Integrative Epidemiology Unit, University of Bristol||The National Institute for Health and Care Research Applied Research Collaboration West (NIHR ARC West) at University Hospitals Bristol and Weston NHS Foundation TrustPopulation Health Sciences, Bristol Medical School, University of Bristol||MRC Integrative Epidemiology Unit, University of Bristol||Department of Surgery, University of Pennsylvania Perelman School of MedicineCentre for Mathematical Sciences, School of Engineering, Computing and Mathematics, University of PlymouthCentre for Longitudinal Studies, UCL Social Research Institute, University College of LondonDepartment of Public Health and Primary Care, University of CambridgeDepartment of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King?ˉs College LondonPopulation Health Sciences, Bristol Medical School, University of Bristol||NIHR Bristol Biomedical Research Centre||Health Data Research UK South-WestDepartment of Public Health and Primary Care, University of CambridgeThe Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of OxfordPopulation Health Sciences, Bristol Medical School, University of Bristol||NIHR Bristol Biomedical Research Centre||Health Data Research UK South-WestThe Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of OxfordThe Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of OxfordNational Institute for Health and Care Excellence||Department of Primary Care and Public Health, Imperial College LondonThe Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of OxfordPopulation Health Sciences, Bristol Medical School, University of Bristol||The National Institute for Health and Care Research Applied Research Collaboration West (NIHR ARC West) at University Hospitals Bristol and Weston NHS Foundation TrustCentre for Mathematical Sciences, School of Engineering, Computing and Mathematics, University of Plymouth||Population Health Sciences, Bristol Medical School, University of BristolInstitute of Health Informatics, University College London||British Heart Foundation Data Science Centre, Health Data Research UK||NIHR University College London Hospitals Biomedical Research Centre (UCLH BRC)||UCL BHF Research Accelerator, University College LondonThe Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of OxfordThe Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of OxfordMRC Unit for Lifelong Health and Ageing, University College LondonPopulation Health Sciences, Bristol Medical School, University of Bristol||The National Institute for Health and Care Research Applied Research Collaboration West (NIHR ARC West) at University Hospitals Bristol and Weston NHS Foundation TrustPopulation Health Sciences, Bristol Medical School, University of Bristol||NIHR Bristol Biomedical Research CentreNational Institute for Health and Care ExcellenceMRC Unit for Lifelong Health and Ageing, University College LondonUsher Institute, The University of Edinburgh
医学研究方法临床医学内科学
Knight Rochelle,Walker Venexia,Riley Stephanie,Silverwood Richard J,Wood Angela M,Steves Claire,Sterne Jonathan AC,Cezard Genevieve,Fisher Louis,Denholm Rachel,Goldacre Ben,Mehrkar Amir,Greaves Felix,Walker Alex,Taylor Kurt,Wei Yinghui,Denaxas Spiros,Bacon Sebastian,Davy Simon,Williams Dylan M,Macleod John,Horne Elsie MF,Willans Robert,Chaturvedi Nish,Sheikh Aziz.Patient characteristics associated with clinically coded long COVID: an OpenSAFELY study using electronic health records[EB/OL].(2025-03-28)[2025-05-12].https://www.medrxiv.org/content/10.1101/2023.06.23.23291776.点此复制
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