Development and validation of prognostic model for predicting mortality of COVID-19 patients in Wuhan, China

• Published in: Scientific reports Vol. 10; no. 1; p. 22451
• Main Authors: Mei, Qi, Wang, Amanda Y., Bryant, Amy, Yang, Yang, Li, Ming, Wang, Fei, Zhao, Jia Wei, Ma, Ke, Wu, Liang, Chen, Huawen, Luo, Jinlong, Du, Shangming, Halfter, Kathrin, Li, Yong, Kurts, Christian, Hu, Guangyuan, Yuan, Xianglin, Li, Jian
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 31.12.2020; Nature Publishing Group; Nature Portfolio
• Subjects: 692/499; 692/53; 692/699/1785; 692/699/255; 692/700; Aged; Aspartate transaminase; Body temperature; China; Coronaviruses; COVID-19; COVID-19 - mortality; Female; Hospitalization - statistics & numerical data; Humanities and Social Sciences; Humans; Lymphocytes; Lymphopenia - pathology; Male; Medical prognosis; Middle Aged; Models, Statistical; Mortality; Mortality risk; multidisciplinary; Multivariate Analysis; Pandemics; Patients; Pneumonia; Prognosis; Public health; Retrospective Studies; Risk Assessment; Risk Factors; Risk groups; SARS-CoV-2; Science; Science (multidisciplinary); Severe acute respiratory syndrome coronavirus 2; Survival Rate; Training; Transaminase; China
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-020-78870-6

Novel coronavirus 2019 (COVID-19) infection is a global public health issue, that has now affected more than 200 countries worldwide and caused a second wave of pandemic. Severe adult respiratory syndrome-CoV-2 (SARS-CoV-2) pneumonia is associated with a high risk of mortality. However, prognostic factors predicting poor clinical outcomes of individual patients with SARS-CoV-2 pneumonia remain under intensive investigation. We conducted a retrospective, multicenter study of patients with SARS-CoV-2 who were admitted to four hospitals in Wuhan, China from December 2019 to February 2020. Mortality at the end of the follow up period was the primary outcome. Factors predicting mortality were also assessed and a prognostic model was developed, calibrated and validated. The study included 492 patients with SARS-CoV-2 who were divided into three cohorts: the training cohort (n = 237), the validation cohort 1 (n = 120), and the validation cohort 2 (n = 135). Multivariate analysis showed that five clinical parameters were predictive of mortality at the end of follow up period, including advanced age [odds ratio (OR), 1.1/years increase ( p  < 0.001)], increased neutrophil-to-lymphocyte ratio [(NLR) OR, 1.14/increase ( p  < 0.001)], elevated body temperature on admission [OR, 1.53/°C increase ( p  = 0.005)], increased aspartate transaminase [OR, 2.47 ( p  = 0.019)], and decreased total protein [OR, 1.69 ( p  = 0.018)]. Furthermore, the prognostic model drawn from the training cohort was validated with validation cohorts 1 and 2 with comparable area under curves (AUC) at 0.912, 0.928, and 0.883, respectively. While individual survival probabilities were assessed, the model yielded a Harrell’s C index of 0.758 for the training cohort, 0.762 for the validation cohort 1, and 0.711 for the validation cohort 2, which were comparable among each other. A validated prognostic model was developed to assist in determining the clinical prognosis for SARS-CoV-2 pneumonia. Using this established model, individual patients categorized in the high risk group were associated with an increased risk of mortality, whereas patients predicted to be in the low risk group had a higher probability of survival.