Journal article 237 views 26 downloads
Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK
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Mike Seaborne ,
Mohamed Mhereeg,
A Walker,
V Walker,
S Denaxas,
Tash Kennedy Kennedy,
S. V Katikireddi,
Sinead Brophy
BMC Medicine, Volume: 21, Issue: 1
Swansea University Authors:
Jonathan Kennedy, Michael Parker , Mike Seaborne , Mohamed Mhereeg, Tash Kennedy Kennedy, Sinead Brophy
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© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made
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DOI (Published version): 10.1186/s12916-023-02897-5
Abstract
Background: To determine the extent and nature of changes associated with COVID-19 infection in terms of healthcare utilisation, this study observed healthcare contact 1 to 4 and 5 to 24 weeks following a COVID-19 diagnosis compared to propensity-matched controls.Methods: Two hundred forty nine thou...
| Published in: | BMC Medicine |
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| ISSN: | 1741-7015 |
| Published: |
Springer Science and Business Media LLC
2023
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa63736 |
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| Abstract: |
Background: To determine the extent and nature of changes associated with COVID-19 infection in terms of healthcare utilisation, this study observed healthcare contact 1 to 4 and 5 to 24 weeks following a COVID-19 diagnosis compared to propensity-matched controls.Methods: Two hundred forty nine thousand three hundred ninety Welsh individuals with a positive reverse transcription–polymerase chain reaction (RT-PCR) test were identified from data from national PCR test results. After elimination criteria, 98,600 positive individuals were matched to test negative and never tested controls using propensity matching. Cohorts were split on test location. Tests could be taken in either the hospital or community. Controls were those who had tested negative in their respective environments. Survival analysis was utilised for first clinicaloutcomes which are grouped into primary and secondary. Primary outcomes include post-viral-illness and fatigue as an indication of long-COVID. Secondary outcomes include clinical terminology concepts for embolism, respiratory conditions, mental health conditions, ft notes, or hospital attendance. Increased instantaneous risk for positive individuals was quantified using hazard ratios (HR) from Cox regression, while absolute risk (AR) and relative risk were quantified using life table analysis.Results: Analysis was conducted using all individuals and stratified by test location. Cases are compared to controls from the same test location. Fatigue (HR: 1.77, 95% CI: 1.34–2.25, p= <0.001) and embolism (HR: 1.50, 95% CI: 1.15–1.97, p=0.003) were more likely to occur in all positive individuals in the first 4 weeks; however, anxiety and depression (HR: 0.83, 95% CI: 0.73–0.95, p=0.007) were less likely. Positive individuals continued to be more at risk of fatigue(HR: 1.47, 95% CI: 1.24–1.75, p= <0.001) and embolism (HR: 1.51, 95% CI: 1.13–2.02, p=0.005) after 4 weeks. All positive individuals are also at greater risk of post-viral illness (HR: 4.57, 95% CI: 1.77–11.80, p=0.002). Despite statistical association between testing positive and several conditions, life table analysis shows that only a small minority of the studypopulation were affected. |
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| College: |
Faculty of Medicine, Health and Life Sciences |
| Funders: |
UKRI, MC_PC_20059, MC_PC_20030. |
| Issue: |
1 |