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

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 syndrom...

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Main Authors: Rulin Wang, Minghui Lin, Shangqiao Yu, Xijuan Xue, Xue Hu, Zhizhong Wang
Format: Article
Language:English
Published: The Journal of Infection in Developing Countries 2025-04-01
Series:Journal of Infection in Developing Countries
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Online Access:https://jidc.org/index.php/journal/article/view/18574
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author Rulin Wang
Minghui Lin
Shangqiao Yu
Xijuan Xue
Xue Hu
Zhizhong Wang
author_facet Rulin Wang
Minghui Lin
Shangqiao Yu
Xijuan Xue
Xue Hu
Zhizhong Wang
author_sort Rulin Wang
collection DOAJ
description 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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spelling doaj-art-3de24a4babaa43ca830b36498a6d4b292025-08-20T02:27:14ZengThe Journal of Infection in Developing CountriesJournal of Infection in Developing Countries1972-26802025-04-01190410.3855/jidc.18574Predictors of post-COVID-19 syndrome: a meta-analysisRulin Wang0Minghui Lin1Shangqiao Yu2Xijuan Xue3Xue Hu4Zhizhong Wang5Department of Nurses at Medical College, Xijing University, Xi’an, Shanxi, ChinaDepartment of Infectious Disease, The Fourth People’s Hospital of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, ChinaDepartment of Nurses at Medical College, Xijing University, Xi’an, Shanxi, ChinaDepartment of Nurses at Medical College, Xijing University, Xi’an, Shanxi, ChinaDepartment of Epidemiology and Statistics, School of Public Health at Guangdong Medical University, Dongguan, Guangdong, ChinaDepartment of Epidemiology and Statistics, School of Public Health at Guangdong Medical University, Dongguan, Guangdong, China 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. https://jidc.org/index.php/journal/article/view/18574Post COVID-19 syndromepredictorsrisk factor
spellingShingle Rulin Wang
Minghui Lin
Shangqiao Yu
Xijuan Xue
Xue Hu
Zhizhong Wang
Predictors of post-COVID-19 syndrome: a meta-analysis
Journal of Infection in Developing Countries
Post COVID-19 syndrome
predictors
risk factor
title Predictors of post-COVID-19 syndrome: a meta-analysis
title_full Predictors of post-COVID-19 syndrome: a meta-analysis
title_fullStr Predictors of post-COVID-19 syndrome: a meta-analysis
title_full_unstemmed Predictors of post-COVID-19 syndrome: a meta-analysis
title_short Predictors of post-COVID-19 syndrome: a meta-analysis
title_sort predictors of post covid 19 syndrome a meta analysis
topic Post COVID-19 syndrome
predictors
risk factor
url https://jidc.org/index.php/journal/article/view/18574
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