The novel coronavirus disease 2019 (COVID-19) spreads rapidly among people and causes a global pandemic. It is of great clinical significance to identify COVID-19 patients with high risk of death.
Of the 2,169 COVID-19 patients, the median age was 61 years and male patients accounted for 48%. A total of 646 patients were diagnosed with severe illness, and 75 patients died. Obvious differences in demographics, clinical characteristics and laboratory examinations were found between survivors and non-survivors. A decision tree classifier, including three biomarkers, neutrophil-to-lymphocyte ratio, C-reactive protein and lactic dehydrogenase, was developed to predict death outcome in severe patients. This model performed well both in train dataset and test dataset. The accuracy of this model was 0.98 and 0.98, respectively.
The machine learning model was robust and effective in predicting the death outcome in severe COVID-19 patients.