Death Risk Analysis for Patients With Severe COVID-19 Pneumonia

Background: Coronavirus Disease 2019 (COVID-19) is currently a global pandemic. Information about the death predicting of severe COVID-19 is not clear. Methods: : 151 in-patients from January 23th to March 8th 2020 were divided into severe and critically severe group, as well as survival and death group. The analysis of differences of clinical and imaging data were performed between groups. The logistic regression analysis of factors associated with death in COVID-19 were conducted, and the prediction model of death risk was developed. Results: : Many clinical and imaging indices were significantly different between groups, including the age, the epidemic history, the past medical history, the duration of symptoms prior to admission, blood routine, inflammatory related factors, Na + , myocardial zymogram, liver and renal function, coagulation function, fraction of inspired oxygen and complications. The proportion of patients in imaging stage III and comprehensive CT scores was increased significantly in death group. The area under receiver operating characteristic curve of the prediction model was 0.9593. Conclusions: : The clinical and imaging data reflect the severity of COVID-19 pneumonia. The prediction model of death risk might be a promising method to help clinicians to quickly identify and screen potential individuals who had a high-risk of death.