Predictors of mortality in patients with coronavirus disease 2019: a systematic review and meta-analysis

Shi, Changcheng; Wang, Limin; Ye, Jian; Gu, Zhichun; Wang, Shuying; Xia, Junbo; Xie, Yaping; Li, Qingyu; Xu, Renjie; Lin, Nengming

BACKGROUND: Coronavirus disease 2019 (COVID-19) is associated with a high mortality rate, especially in patients with severe illness. We conducted a systematic review and meta-analysis to assess the potential predictors of mortality in patients with COVID-19. METHODS: PubMed, EMBASE, the Cochrane Library, and three electronic Chinese databases were searched from December 1, 2019 to April 29, 2020. Eligible studies reporting potential predictors of mortality in patients with COVID-19 were identified. Unadjusted prognostic effect estimates were pooled using the random-effects model if data from at least two studies were available. Adjusted prognostic effect estimates were presented by qualitative analysis. RESULTS: Thirty-six observational studies were identified, of which 27 were included in the meta-analysis. A total of 106 potential risk factors were tested, and the following important predictors were associated with mortality: advanced age, male sex, current smoking status, preexisting comorbidities (especially chronic kidney, respiratory, and cardio-cerebrovascular diseases), symptoms of dyspnea, complications during hospitalization, corticosteroid therapy and a severe condition. Additionally, a series of abnormal laboratory biomarkers of hematologic parameters, hepatorenal function, inflammation, coagulation, and cardiovascular injury were also associated with fatal outcome. CONCLUSION: We identified predictors of mortality in patients with COVID-19. These findings could help healthcare providers take appropriate measures and improve clinical outcomes in such patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-021-06369-0.