Clinical features predicting mortality risk in older patients with COVID-19
Jing Zhou, Lili Huang, Jin Chen, Xiaowei Yuan, Qinhua Shen, Dong Su, Cheng Bei, Tangmeng Guo
Abstract
BACKGROUND: Since December 2019, the cumulative number of coronavirus disease 2019 (COVID-19) deaths worldwide has reached 1,013,100 and continues to increase as of writing. Of these deaths, more than 90% are people aged 60 and older. Therefore, there is a need for an easy-to-use clinically predictive tool for predicting mortality risk in older individuals with COVID-19. OBJECTIVE: To explore an easy-to-use clinically predictive tool that may be utilized in predicting mortality risk in older patients with COVID-19. METHODS: A retrospective analysis of 118 older patients with COVID-19 admitted to the Union Dongxihu Hospital, Huazhong University of Science and Technology, Wuhan, China from 12 January to 26 February 2020. The main results of epidemiological, demographic, clinical and laboratory tests on admission were collected and compared between dying and discharged patients. RESULTS: < .001). Bootstrap validation generated the similar sensitivity and specificity. CONCLUSIONS: We designed an easy-to-use clinically predictive tool for early identification and stratified treatment of older patients with severe COVID-19.