Predictors of post-COVID-19 syndrome: a meta-analysis

Abstract

Introduction: Post Coronavirus Disease 2019 (COVID-19) Syndrome also known as long COVID-19 would affect survivors of various patients. At present, the evidence for predicting a poor prognosis of COVID-19 remains insufficient. This study aims to explore potential predictors of post-COVID-19 syndrome. Methodology: A systematic review process and meta-analysis method are applied to identify the predictors. Systematic searches were conducted without language restrictions from December 1, 2019, to February 28, 2022, on PubMed, Embase, Google Scholar, Web of Science, and Cochrane Library using specific keywords relevant to our targets. The Newcastle Ottawa Scale observational research tool was used to assess study quality and the R (4.1.1) package meta was used for statistical analysis. Results: Our meta-analysis of 14 studies showed that females (OR = 1.42, 95% CI: 1.19-1.70), the severity of patients (OR = 2.43, 95% CI: 1.26-4.68), comorbidity (OR = 2.08, 95% CI: 1.29-3.35), dyspnea (OR = 2.02, 95% CI: 1.34-3.04) associated with a higher risk of post-COVID-19 syndrome. Conclusions: Our study showed that females, the severity of COVID-19, comorbidity, and dyspnea were associated with a higher risk of post-COVID-19 syndrome. More attention should be paid to these factors to prevent and treat post-COVID-19 syndrome.