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Comorbidities' potential impacts on severe and non-severe patients with COVID-19: A systematic review and meta-analysis.
Cheng, Sixiang; Zhao, Yuxin; Wang, Fenxiao; Chen, Yan; Kaminga, Atipatsa Chiwanda; Xu, Huilan.
  • Cheng S; Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, Hunan Province.
  • Zhao Y; College of Data Science and Information Engineering, Guizhou Minzu University, Guiyang, Guizhou Province.
  • Wang F; Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, Hunan Province.
  • Chen Y; Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, Hunan Province.
  • Kaminga AC; College of Data Science and Information Engineering, Guizhou Minzu University, Guiyang, Guizhou Province.
  • Xu H; Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, Hunan, China.
Medicine (Baltimore) ; 100(12): e24971, 2021 Mar 26.
Article in English | MEDLINE | ID: covidwho-1150004
ABSTRACT

BACKGROUND:

An ongoing outbreak of pneumonia associated with the severe acute respiratory coronavirus (SARS-CoV-2) emerged in December 2019 in Wuhan, China. Epidemiologic evidence suggests that patients with comorbidities and novel coronavirus disease 2019 (COVID-19) infection may have poor survival outcomes. However, the risk of these coexisting medical conditions in severe and non-severe cases has not been systematically reported.

PURPOSE:

The present study aimed to estimate the association of chronic comorbidities in severe and non-severe cases.

METHODS:

A literature search was conducted using the databases PubMed, Embase, China National Knowledge Infrastructure (CNKI), and Wanfang Database, Chinese Scientific Journals Full-text Database (CQVIP) from the inception dates to April 1, 2020, to identify cohort studies assessing comorbidity and risk of adverse outcome. Either a fixed- or random-effects model was used to calculate the overall combined risk estimates.

RESULTS:

A total of 22 studies involving 3286 patients with laboratory-confirmed COVID-19 were included in the analysis. Overall, compared with the patients with non-severe cases, the pooled odds ratios (ORs) of hypertension, diabetes mellitus, and cardiovascular, cerebrovascular, and respiratory diseases in patients with severe cases were 2.79 (95% confidence intervals [95% CI] 1.66-4.69), 1.64 (95% CI 2.30-1.08), 1.79 (95% CI 1.08-2.96), 3.92 (95% CI 2.45-6.28), and 1.98 (95% CI 1.26-3.12), respectively.

CONCLUSIONS:

This meta-analysis supports the finding that chronic comorbidities may contribute to severe outcome in patients with COVID-19. According to the findings of the present study, old age and 2 or more comorbidities are significantly impactful to COVID-19 outcomes in hospitalized patients in China.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Comorbidity / COVID-19 Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Limits: Humans Language: English Journal: Medicine (Baltimore) Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Comorbidity / COVID-19 Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Limits: Humans Language: English Journal: Medicine (Baltimore) Year: 2021 Document Type: Article