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Comorbidities’ potential impacts on severe and non-severe patients with COVID-19: A systematic review and meta-analysis
Authors:Sixiang Cheng  Yuxin Zhao  Fenxiao Wang  Yan Chen  Atipatsa Chiwanda Kaminga  Huilan Xu
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.
Keywords:comorbidities  COVID-19  epidemiological  meta-analysis  SARS-CoV-2
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