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

Rulin Wang; Minghui Lin; Shangqiao Yu; Xijuan Xue; Xue Hu; Zhizhong Wang

doi:10.3855/jidc.18574

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

Authors

Rulin Wang Department of Nurses at Medical College, Xijing University, Xi’an, Shanxi, China https://orcid.org/0009-0007-5948-3202
Minghui Lin Department of Infectious Disease, The Fourth People’s Hospital of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China
Shangqiao Yu Department of Nurses at Medical College, Xijing University, Xi’an, Shanxi, China
Xijuan Xue Department of Nurses at Medical College, Xijing University, Xi’an, Shanxi, China
Xue Hu Department of Epidemiology and Statistics, School of Public Health at Guangdong Medical University, Dongguan, Guangdong, China https://orcid.org/0000-0002-7344-9189
Zhizhong Wang Department of Epidemiology and Statistics, School of Public Health at Guangdong Medical University, Dongguan, Guangdong, China https://orcid.org/0000-0002-0612-3218

DOI:

https://doi.org/10.3855/jidc.18574

Keywords:

Post COVID-19 syndrome, predictors, risk factor

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.

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Published

2025-04-29

How to Cite

Wang R, Lin M, Yu S, Xue X, Hu X, Wang Z (2025) Predictors of post-COVID-19 syndrome: a meta-analysis. J Infect Dev Ctries 19:490–497. doi: 10.3855/jidc.18574

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Issue

Vol. 19 No. 04: April 2025

Section

Coronavirus Pandemic

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