Exploration of prognostic factors for critical COVID-19 patients：a nomogram analysis

To discuss influencing factors on critical COVID-19 patient’s prognosis, construct a basic model and predict their mortality risks. Retrospectively analyzed the general condition and respective laboratory biomarkers of critical patients with duration≥24 h from Feb. 10th, 2020 to Mar. 30th, 2020 to separate them into a survival group and death group based on their clinical features. Multiple logistic regression analysis was performed to assess risk factors for critical COVID-19 patient’s and a nomogram was constructed based on screened risk factors. A receiver operating curve (ROC) was created to evaluate the accuracy of the nomogram. Multi-factor Logistic recovery analysis results show: Age, Peripheral blood leucocyte count,Lymphocyte percentage, Thrombocyte count and Hyper C-reactive protein are single danger factors of critical COVID-19 patient’s mortality risk (p＜0.05). ROC curve indicates Nomogram predictive model AUC is 0.958 (95%CI: 0.923-0.993), which has high predictive value. Findings from this study suggest advanced age, high peripheral blood leucocyte count, high hyper C-reactive protein, low lymphocyte percentage and low thrombocyte count are risk factors of critical COVID-19 patient’s death.The Nomogram model is helpful for timely intervention to reduce the incidence of critical COVID-19 patients.