Predictive model and risk factors for case fatality of COVID-19: a cohort of 21,392 cases in Hubei, China

Background An increasing number of patients are being killed by coronavirus disease 2019 (COVID-19);however, risk factors for the case fatality of COVID-19 have not yet been well studied Methods A total of 21,392 COVID-19 cases were recruited in the Hubei Province of China between December 2019 and February 2020, and followed up until March 18, 2020 We adopted Cox regression models to investigate the risk factors for the case fatality and predicted the death probability under specific combinations of key predictors Results Among the 21,392 patients, 1,020 (4 77%) died of COVID-19 Multivariable analyses showed that factors including age [≥ 60 years versus 39°C versus 10 ×109/L versus (4-10) ×109/L, HR: 1 69;95% CI: 1 35, 2 13), and lymphocyte counts (<0 8 ×109/L versus (0 8-4) ×109/L, HR: 1 26;95% CI: 1 06, 1 50) were significantly associated with case fatality of COVID-19 patients Individuals of an older age, who were male, with comorbidities, and had a critical illness had the highest death probability, with 21%, 36%, 46%, and 54% within 1-4 weeks after the symptom onset Interpretation Risk factors, including demographic characteristics, clinical symptoms, and laboratory factors were confirmed to be important determinants of fatality of COVID-19 Our predictive model can provide scientific evidence for a more rational, evidence-driven allocation of scarce medical resources to reduce the fatality of COVID-19