Risk Factors Associated with Clinical Outcomes in 323 COVID-19 Hospitalized Patients in Wuhan, China

Hu, Ling; Chen, Shaoqiu; Fu, Yuanyuan; Gao, Zitong; Long, Hui; Wang, Jian-ming; Ren, Hong-wei; Zuo, Yi; Li, Huan; Wang, Jie; Xu, Qing-bang; Yu, Wen-xiong; Liu, Jia; Shao, Chen; Hao, Jun-jie; Wang, Chuan-zhen; Ma, Yao; Wang, Zhanwei; Yanagihara, Richard; Deng, Youping

BACKGROUND: With evidence of sustained transmission in more than 190 countries, coronavirus disease 2019 (COVID-19) has been declared a global pandemic. Data are urgently needed about risk factors associated with clinical outcomes. METHODS: A retrospective review of 323 hospitalized patients with COVID-19 in Wuhan was conducted. Patients were classified into three disease severity groups (non-severe, severe, and critical), based on initial clinical presentation. Clinical outcomes were designated as favorable and unfavorable, based on disease progression and response to treatments. Logistic regression models were performed to identify risk factors associated with clinical outcomes, and log-rank test was conducted for the association with clinical progression. RESULTS: Current standard treatments did not show significant improvement in patient outcomes. By univariate logistic regression analysis, 27 risk factors were significantly associated with clinical outcomes. Multivariate regression indicated age over 65 years (p<0.001), smoking (p=0.001), critical disease status (p=0.002), diabetes (p=0.025), high hypersensitive troponin I (>0.04 pg/mL, p=0.02), leukocytosis (>10 x 10(9)/L, p<0.001) and neutrophilia (>75 x 10(9)/L, p<0.001) predicted unfavorable clinical outcomes. By contrast, the administration of hypnotics was significantly associated with favorable outcomes (p<0.001), which was confirmed by survival analysis. CONCLUSIONS: Hypnotics may be an effective ancillary treatment for COVID-19. We also found novel risk factors, such as higher hypersensitive troponin I, predicted poor clinical outcomes. Overall, our study provides useful data to guide early clinical decision making to reduce mortality and improve clinical outcomes of COVID-19.