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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The Journal of Infection in Developing Countries
2025-04-01
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| 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 |
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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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| format | Article |
| id | doaj-art-3de24a4babaa43ca830b36498a6d4b29 |
| institution | OA Journals |
| issn | 1972-2680 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | The Journal of Infection in Developing Countries |
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| series | Journal of Infection in Developing Countries |
| 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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