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Risk factors and predictors associated with the severity of COVID-19 in China: a systematic review, meta-analysis, and meta-regression
Since December 2019, the pneumonia cases infected with 2019 novel coronavirus have appeared, posing a critical threat to global health. In this study, we performed a meta-analysis to discover the different clinical characteristics between severe and non-severe patients with COVID-19 to find the pote...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797827/ https://www.ncbi.nlm.nih.gov/pubmed/33447431 http://dx.doi.org/10.21037/jtd-20-1743 |
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author | Zhang, Tao Huang, Wei-Sen Guan, Weijie Hong, Ziying Gao, Jiabo Gao, Guoying Wu, Guofeng Qin, Yin-Yin |
author_facet | Zhang, Tao Huang, Wei-Sen Guan, Weijie Hong, Ziying Gao, Jiabo Gao, Guoying Wu, Guofeng Qin, Yin-Yin |
author_sort | Zhang, Tao |
collection | PubMed |
description | Since December 2019, the pneumonia cases infected with 2019 novel coronavirus have appeared, posing a critical threat to global health. In this study, we performed a meta-analysis to discover the different clinical characteristics between severe and non-severe patients with COVID-19 to find the potential risk factors and predictors of this disease’s severity, as well as to serve as a guidance for subsequent epidemic prevention and control work. PubMed, Cochrane Library, Medline, Embase and other databases were searched to collect studies on the difference of clinical characteristics of severe and non-severe patients. Meta-analysis was performed using RevMan 5.3 software, and the funnel plots could be made to evaluate the publication bias. P>0.05 means no statistical significance. Furthermore, a meta-regression analysis was performed by using Stata 15.0 to find the potential factors of the high degree of heterogeneity (I(2)>50%). Sixteen studies have been included, with 1,172 severe patients and 2,803 non-severe patients. Compared with non-severe patients, severe patients were more likely to have the symptoms of dyspnea, hemoptysis, and the complications of ARDS, shock, secondary infection, acute kidney injury, and acute cardiac injury. Interestingly, the former smokers were more prevalent in severe cases as compared to non-severe cases, but there was no difference between the two groups of ‘current smokers’. Except for chronic liver disease and chronic kidney disease, the underlying comorbidities of hypertension, diabetes, cardiovascular disease, chronic obstructive pulmonary disease (COPD), malignancy, cerebrovascular disease, and HIV can make the disease worse. In terms of laboratory indicators, the decreased lymphocyte and platelet count, and the increased levels of white blood cell (WBC), D-dimer, creatine kinase, lactate dehydrogenase, procalcitonin, alanine aminotransferase, aspartate aminotransferase, and C-reactive protein were more prevalent in severe patients. Meta-regression analysis showed that patient age, gender, and proportion of severe cases did not significantly impact on the outcomes of any clinical indexes that showed high degree of heterogeneity in the meta-analysis. In conclusion, the severity of COVID-19 could be evaluated by, radiologic finding, some symptoms like dyspnea and hemoptysis, some laboratory indicators, and smoking history, especially the ex-smokers. Compared with non-severe patients, severe patients were more likely to have complications and comorbidities including hypertension, cardiovascular disease etc., which were the risk factors for the disease to be severer, but the chronic liver disease and chronic kidney disease were not associated the severity of COVID-19 in China. |
format | Online Article Text |
id | pubmed-7797827 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-77978272021-01-13 Risk factors and predictors associated with the severity of COVID-19 in China: a systematic review, meta-analysis, and meta-regression Zhang, Tao Huang, Wei-Sen Guan, Weijie Hong, Ziying Gao, Jiabo Gao, Guoying Wu, Guofeng Qin, Yin-Yin J Thorac Dis Review Article Since December 2019, the pneumonia cases infected with 2019 novel coronavirus have appeared, posing a critical threat to global health. In this study, we performed a meta-analysis to discover the different clinical characteristics between severe and non-severe patients with COVID-19 to find the potential risk factors and predictors of this disease’s severity, as well as to serve as a guidance for subsequent epidemic prevention and control work. PubMed, Cochrane Library, Medline, Embase and other databases were searched to collect studies on the difference of clinical characteristics of severe and non-severe patients. Meta-analysis was performed using RevMan 5.3 software, and the funnel plots could be made to evaluate the publication bias. P>0.05 means no statistical significance. Furthermore, a meta-regression analysis was performed by using Stata 15.0 to find the potential factors of the high degree of heterogeneity (I(2)>50%). Sixteen studies have been included, with 1,172 severe patients and 2,803 non-severe patients. Compared with non-severe patients, severe patients were more likely to have the symptoms of dyspnea, hemoptysis, and the complications of ARDS, shock, secondary infection, acute kidney injury, and acute cardiac injury. Interestingly, the former smokers were more prevalent in severe cases as compared to non-severe cases, but there was no difference between the two groups of ‘current smokers’. Except for chronic liver disease and chronic kidney disease, the underlying comorbidities of hypertension, diabetes, cardiovascular disease, chronic obstructive pulmonary disease (COPD), malignancy, cerebrovascular disease, and HIV can make the disease worse. In terms of laboratory indicators, the decreased lymphocyte and platelet count, and the increased levels of white blood cell (WBC), D-dimer, creatine kinase, lactate dehydrogenase, procalcitonin, alanine aminotransferase, aspartate aminotransferase, and C-reactive protein were more prevalent in severe patients. Meta-regression analysis showed that patient age, gender, and proportion of severe cases did not significantly impact on the outcomes of any clinical indexes that showed high degree of heterogeneity in the meta-analysis. In conclusion, the severity of COVID-19 could be evaluated by, radiologic finding, some symptoms like dyspnea and hemoptysis, some laboratory indicators, and smoking history, especially the ex-smokers. Compared with non-severe patients, severe patients were more likely to have complications and comorbidities including hypertension, cardiovascular disease etc., which were the risk factors for the disease to be severer, but the chronic liver disease and chronic kidney disease were not associated the severity of COVID-19 in China. AME Publishing Company 2020-12 /pmc/articles/PMC7797827/ /pubmed/33447431 http://dx.doi.org/10.21037/jtd-20-1743 Text en 2020 Journal of Thoracic Disease. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Review Article Zhang, Tao Huang, Wei-Sen Guan, Weijie Hong, Ziying Gao, Jiabo Gao, Guoying Wu, Guofeng Qin, Yin-Yin Risk factors and predictors associated with the severity of COVID-19 in China: a systematic review, meta-analysis, and meta-regression |
title | Risk factors and predictors associated with the severity of COVID-19 in China: a systematic review, meta-analysis, and meta-regression |
title_full | Risk factors and predictors associated with the severity of COVID-19 in China: a systematic review, meta-analysis, and meta-regression |
title_fullStr | Risk factors and predictors associated with the severity of COVID-19 in China: a systematic review, meta-analysis, and meta-regression |
title_full_unstemmed | Risk factors and predictors associated with the severity of COVID-19 in China: a systematic review, meta-analysis, and meta-regression |
title_short | Risk factors and predictors associated with the severity of COVID-19 in China: a systematic review, meta-analysis, and meta-regression |
title_sort | risk factors and predictors associated with the severity of covid-19 in china: a systematic review, meta-analysis, and meta-regression |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797827/ https://www.ncbi.nlm.nih.gov/pubmed/33447431 http://dx.doi.org/10.21037/jtd-20-1743 |
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