Comorbidities and the risk of severe or fatal outcomes associated with coronavirus disease 2019: A systematic review and meta-analysis.
Identifieur interne : 000006 ( Main/Corpus ); précédent : 000005; suivant : 000007Comorbidities and the risk of severe or fatal outcomes associated with coronavirus disease 2019: A systematic review and meta-analysis.
Auteurs : Yue Zhou ; Qing Yang ; Jingwei Chi ; Bingzi Dong ; Wenshan Lv ; Liyan Shen ; Yangang WangSource :
- International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases [ 1878-3511 ] ; 2020.
Abstract
OBJECTIVES
Existing findings regarding the relationship between comorbidities and Covid-19 severity is inconsistent and insufficient. The present study aimed to evaluate the association between different comorbidities and the severity of Covid-19.
METHODS
PubMed, EMBASE, and the Cochrane Library were searched to identify studies reporting on the rate of comorbidities in Covid-19 patients with severe/fatal outcomes. Subgroup analyses were conducted according to disease severity, and the country of residence. Odds ratio (OR) with 95% confidence intervals (CI) were pooled using random-effects models.
RESULTS
A total of 34 eligible studies were identified. In patients with severe/fatal Covid-19, the most prevalent chronic comorbidity was obesity (42%, 95CI 34-49%) and hypertension (40%, 95%CI 35-45%), followed by diabetes (17%, 95%CI 15-20%), cardiovascular disease (13%, 95%CI 11-15%), respiratory disease (8%, 95%CI 6-10%), cerebrovascular disease (6%, 95%CI 4-8%), malignancy (4%, 95% CI 3-6%), kidney disease (3%, 95%CI 2-4%), and liver disease (2%, 95%CI 1-3%). In order of the prediction, the pooled ORs of the chronic respiratory disease, hypertension, cardiovascular disease, kidney disease, cerebrovascular disease, malignancy, diabetes, and obesity in patients with severe or fatal Covid-19 were (OR 3.56, 95%CI 2.87-4.41), (OR 3.17, 95%CI 2.46-4.08), (OR 3.13, 95%CI 2.65-3.70), (OR 3.02, 95%CI 2.23-4.08), (OR 2.74, 95%CI 1.59-4.74), (OR 2.73, 95%CI 1.73-4.21), (OR 2.63, 95%CI 2.08-3.33), and (OR 1.72, 95%CI 1.04-2.85), respectively, compared with patients with non-severe/fatal Covid-19. No correlation was observed between liver disease and Covid-19 aggravation (OR 1.54, 95%CI 0.95-2.49).
CONCLUSIONS
Chronic comorbidities, including obesity, hypertension, diabetes, cardia-cerebrovascular disease, respiratory disease, kidney disease, and malignancy, are clinical risk factors of severe or fatal outcomes associated with Covid-19, with obesity being the most prevalent, and respiratory disease being the most strongly predictive. Knowledge of these risk factors can help clinicians better identify and guide the high-risk populations.
DOI: 10.1016/j.ijid.2020.07.029
PubMed: 32721533
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Comorbidities and the risk of severe or fatal outcomes associated with coronavirus disease 2019: A systematic review and meta-analysis.</title><author><name sortKey="Zhou, Yue" sort="Zhou, Yue" uniqKey="Zhou Y" first="Yue" last="Zhou">Yue Zhou</name><affiliation><nlm:affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China.</nlm:affiliation></affiliation></author><author><name sortKey="Yang, Qing" sort="Yang, Qing" uniqKey="Yang Q" first="Qing" last="Yang">Qing Yang</name><affiliation><nlm:affiliation>Institute of Biophysics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China.</nlm:affiliation></affiliation></author><author><name sortKey="Chi, Jingwei" sort="Chi, Jingwei" uniqKey="Chi J" first="Jingwei" last="Chi">Jingwei Chi</name><affiliation><nlm:affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China.</nlm:affiliation></affiliation></author><author><name sortKey="Dong, Bingzi" sort="Dong, Bingzi" uniqKey="Dong B" first="Bingzi" last="Dong">Bingzi Dong</name><affiliation><nlm:affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China.</nlm:affiliation></affiliation></author><author><name sortKey="Lv, Wenshan" sort="Lv, Wenshan" uniqKey="Lv W" first="Wenshan" last="Lv">Wenshan Lv</name><affiliation><nlm:affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China.</nlm:affiliation></affiliation></author><author><name sortKey="Shen, Liyan" sort="Shen, Liyan" uniqKey="Shen L" first="Liyan" last="Shen">Liyan Shen</name><affiliation><nlm:affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China. Electronic address: sly1003@126.com.</nlm:affiliation></affiliation></author><author><name sortKey="Wang, Yangang" sort="Wang, Yangang" uniqKey="Wang Y" first="Yangang" last="Wang">Yangang Wang</name><affiliation><nlm:affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China. Electronic address: 15315620815@163.com.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:32721533</idno><idno type="pmid">32721533</idno><idno type="doi">10.1016/j.ijid.2020.07.029</idno><idno type="wicri:Area/Main/Corpus">000006</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000006</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Comorbidities and the risk of severe or fatal outcomes associated with coronavirus disease 2019: A systematic review and meta-analysis.</title><author><name sortKey="Zhou, Yue" sort="Zhou, Yue" uniqKey="Zhou Y" first="Yue" last="Zhou">Yue Zhou</name><affiliation><nlm:affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China.</nlm:affiliation></affiliation></author><author><name sortKey="Yang, Qing" sort="Yang, Qing" uniqKey="Yang Q" first="Qing" last="Yang">Qing Yang</name><affiliation><nlm:affiliation>Institute of Biophysics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China.</nlm:affiliation></affiliation></author><author><name sortKey="Chi, Jingwei" sort="Chi, Jingwei" uniqKey="Chi J" first="Jingwei" last="Chi">Jingwei Chi</name><affiliation><nlm:affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China.</nlm:affiliation></affiliation></author><author><name sortKey="Dong, Bingzi" sort="Dong, Bingzi" uniqKey="Dong B" first="Bingzi" last="Dong">Bingzi Dong</name><affiliation><nlm:affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China.</nlm:affiliation></affiliation></author><author><name sortKey="Lv, Wenshan" sort="Lv, Wenshan" uniqKey="Lv W" first="Wenshan" last="Lv">Wenshan Lv</name><affiliation><nlm:affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China.</nlm:affiliation></affiliation></author><author><name sortKey="Shen, Liyan" sort="Shen, Liyan" uniqKey="Shen L" first="Liyan" last="Shen">Liyan Shen</name><affiliation><nlm:affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China. Electronic address: sly1003@126.com.</nlm:affiliation></affiliation></author><author><name sortKey="Wang, Yangang" sort="Wang, Yangang" uniqKey="Wang Y" first="Yangang" last="Wang">Yangang Wang</name><affiliation><nlm:affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China. Electronic address: 15315620815@163.com.</nlm:affiliation></affiliation></author></analytic><series><title level="j">International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases</title><idno type="eISSN">1878-3511</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>OBJECTIVES</b></p><p>Existing findings regarding the relationship between comorbidities and Covid-19 severity is inconsistent and insufficient. The present study aimed to evaluate the association between different comorbidities and the severity of Covid-19.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>PubMed, EMBASE, and the Cochrane Library were searched to identify studies reporting on the rate of comorbidities in Covid-19 patients with severe/fatal outcomes. Subgroup analyses were conducted according to disease severity, and the country of residence. Odds ratio (OR) with 95% confidence intervals (CI) were pooled using random-effects models.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>A total of 34 eligible studies were identified. In patients with severe/fatal Covid-19, the most prevalent chronic comorbidity was obesity (42%, 95CI 34-49%) and hypertension (40%, 95%CI 35-45%), followed by diabetes (17%, 95%CI 15-20%), cardiovascular disease (13%, 95%CI 11-15%), respiratory disease (8%, 95%CI 6-10%), cerebrovascular disease (6%, 95%CI 4-8%), malignancy (4%, 95% CI 3-6%), kidney disease (3%, 95%CI 2-4%), and liver disease (2%, 95%CI 1-3%). In order of the prediction, the pooled ORs of the chronic respiratory disease, hypertension, cardiovascular disease, kidney disease, cerebrovascular disease, malignancy, diabetes, and obesity in patients with severe or fatal Covid-19 were (OR 3.56, 95%CI 2.87-4.41), (OR 3.17, 95%CI 2.46-4.08), (OR 3.13, 95%CI 2.65-3.70), (OR 3.02, 95%CI 2.23-4.08), (OR 2.74, 95%CI 1.59-4.74), (OR 2.73, 95%CI 1.73-4.21), (OR 2.63, 95%CI 2.08-3.33), and (OR 1.72, 95%CI 1.04-2.85), respectively, compared with patients with non-severe/fatal Covid-19. No correlation was observed between liver disease and Covid-19 aggravation (OR 1.54, 95%CI 0.95-2.49).</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>Chronic comorbidities, including obesity, hypertension, diabetes, cardia-cerebrovascular disease, respiratory disease, kidney disease, and malignancy, are clinical risk factors of severe or fatal outcomes associated with Covid-19, with obesity being the most prevalent, and respiratory disease being the most strongly predictive. Knowledge of these risk factors can help clinicians better identify and guide the high-risk populations.</p></div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32721533</PMID><DateRevised><Year>2020</Year><Month>07</Month><Day>29</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1878-3511</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year><Month>Jul</Month><Day>25</Day></PubDate></JournalIssue><Title>International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases</Title><ISOAbbreviation>Int. J. Infect. Dis.</ISOAbbreviation></Journal><ArticleTitle>Comorbidities and the risk of severe or fatal outcomes associated with coronavirus disease 2019: A systematic review and meta-analysis.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">S1201-9712(20)30572-5</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.ijid.2020.07.029</ELocationID><Abstract><AbstractText Label="OBJECTIVES" NlmCategory="OBJECTIVE">Existing findings regarding the relationship between comorbidities and Covid-19 severity is inconsistent and insufficient. The present study aimed to evaluate the association between different comorbidities and the severity of Covid-19.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">PubMed, EMBASE, and the Cochrane Library were searched to identify studies reporting on the rate of comorbidities in Covid-19 patients with severe/fatal outcomes. Subgroup analyses were conducted according to disease severity, and the country of residence. Odds ratio (OR) with 95% confidence intervals (CI) were pooled using random-effects models.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">A total of 34 eligible studies were identified. In patients with severe/fatal Covid-19, the most prevalent chronic comorbidity was obesity (42%, 95CI 34-49%) and hypertension (40%, 95%CI 35-45%), followed by diabetes (17%, 95%CI 15-20%), cardiovascular disease (13%, 95%CI 11-15%), respiratory disease (8%, 95%CI 6-10%), cerebrovascular disease (6%, 95%CI 4-8%), malignancy (4%, 95% CI 3-6%), kidney disease (3%, 95%CI 2-4%), and liver disease (2%, 95%CI 1-3%). In order of the prediction, the pooled ORs of the chronic respiratory disease, hypertension, cardiovascular disease, kidney disease, cerebrovascular disease, malignancy, diabetes, and obesity in patients with severe or fatal Covid-19 were (OR 3.56, 95%CI 2.87-4.41), (OR 3.17, 95%CI 2.46-4.08), (OR 3.13, 95%CI 2.65-3.70), (OR 3.02, 95%CI 2.23-4.08), (OR 2.74, 95%CI 1.59-4.74), (OR 2.73, 95%CI 1.73-4.21), (OR 2.63, 95%CI 2.08-3.33), and (OR 1.72, 95%CI 1.04-2.85), respectively, compared with patients with non-severe/fatal Covid-19. No correlation was observed between liver disease and Covid-19 aggravation (OR 1.54, 95%CI 0.95-2.49).</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Chronic comorbidities, including obesity, hypertension, diabetes, cardia-cerebrovascular disease, respiratory disease, kidney disease, and malignancy, are clinical risk factors of severe or fatal outcomes associated with Covid-19, with obesity being the most prevalent, and respiratory disease being the most strongly predictive. Knowledge of these risk factors can help clinicians better identify and guide the high-risk populations.</AbstractText><CopyrightInformation>Copyright © 2020. Published by Elsevier Ltd.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Zhou</LastName><ForeName>Yue</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Yang</LastName><ForeName>Qing</ForeName><Initials>Q</Initials><AffiliationInfo><Affiliation>Institute of Biophysics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chi</LastName><ForeName>Jingwei</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Dong</LastName><ForeName>Bingzi</ForeName><Initials>B</Initials><AffiliationInfo><Affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lv</LastName><ForeName>Wenshan</ForeName><Initials>W</Initials><AffiliationInfo><Affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Shen</LastName><ForeName>Liyan</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China. Electronic address: sly1003@126.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Yangang</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Department of Endocrinology, Affiliated Hospital of Medical College Qingdao University, Qingdao, China. 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