Sarri, Grammati; Liu, Wei; Zabotka, Luke; Freitag, Andreas; Claire, Ravinder; Wangge, Grace; Elvidge, Jamie; Dawoud, Dalia; Bennett, Dimitri; Wen, Xuerong; +11 more... Li, Xiaojuan; Rentsch, Christopher T; Uddin, Md Jamal; Ali, M Sanni; Gokhale, Mugdha; Déruaz-Luyet, Anouk; Moga, Daniela C; Guo, Jeff Jianfei; Zullo, Andrew R; Patorno, Elisabetta; Lin, Kueiyu Joshua; (2023) Prognostic Factors of COVID-19: An Umbrella Review Endorsed by the International Society for Pharmacoepidemiology. Clinical pharmacology and therapeutics, 114 (3). pp. 604-613. ISSN 0009-9236 DOI: https://doi.org/10.1002/cpt.2977
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Abstract
During the coronavirus disease 2019 (COVID-19) pandemic, the urgency for updated evidence to inform public health and clinical care placed systematic literature reviews (SLRs) at the cornerstone of research. We aimed to summarize evidence on prognostic factors for COVID-19 outcomes through published SLRs and to critically assess quality elements in the findings' interpretation. An umbrella review was conducted via electronic databases from January 2020 to April 2022. All SLRs (and meta-analyses) in English were considered. Data screening and extraction were conducted by two independent reviewers. AMSTAR 2 tool was used to assess SLR quality. The study was registered with PROSPERO (CRD4202232576). Out of 4,564 publications, 171 SLRs were included of which 3 were umbrella reviews. Our primary analysis included 35 SLRs published in 2022, which incorporated studies since the beginning of the pandemic. Consistent findings showed that, for adults, older age, obesity, heart disease, diabetes, and cancer were more strongly predictive of risk of hospitalization, intensive care unit admission, and mortality due to COVID-19. Male sex was associated with higher risk of short-term adverse outcomes, but female sex was associated with higher risk of long COVID. For children, socioeconomic determinants that may unravel COVID-19 disparities were rarely reported. This review highlights key prognostic factors of COVID-19, which can help clinicians and health officers identify high-risk groups for optimal care. Findings can also help optimize confounding adjustment and patient phenotyping in comparative effectiveness research. A living SLR approach may facilitate dissemination of new findings. This paper is endorsed by the International Society for Pharmacoepidemiology.
Item Type | Article |
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Faculty and Department |
Faculty of Epidemiology and Population Health > Dept of Non-Communicable Disease Epidemiology Faculty of Infectious and Tropical Diseases > Dept of Disease Control |
Research Centre |
EHR Research Group Covid-19 Research |
PubMed ID | 37342987 |
Elements ID | 205378 |
Official URL | http://dx.doi.org/10.1002/cpt.2977 |
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Filename: Sarri-etal-2023-Prognostic-factors-of-covid-19.pdf
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