Development of Predictive Nomogram for ICU Mortality in Severe COVID-19

Background: Reliable prediction tools for ICU mortality within severe Covid-19 population have not yet been definitely established. Methods: We enrolled 91 severe Covid-19 patients admitted to the ICU of Jinyintan Hospital (Wuhan, China) between December 29, 2019 and April 14, 2020. All the baseline characteristics that were different between non-survivors and survivors with p < 0.1 were introduced into multivariate logistic regression to identify independent risk factors for ICU mortality. Odds ratios (ORs) with 95% confidence intervals (CIs) were respectively calculated. Based on the results of multivariate logistic regression, we developed a predictive nomogram, and performed ROC curve analyses to evaluate its predictive performance. Findings: ICU mortality in severe Covid-19 of our cohort was 57.1% (52/91). Multivariate logistic regression identified sum of APACHE II and SOFA score within 24 hours after ICU admission to be an independent risk factor of ICU mortality (adjusted OR: 1.134; 95% CI:1.042–1.234; p = 0.004) after adjusting age, underlying cardiovascular disease, comorbid renal disease, interval days from symptom onset to hospital admission, and serum amyloid protein level. ROC curve analyses confirmed our nomogram to be a superior predictor with a higher performance (AUC: 0.875; 95% CI: 0.801–0.949) over APACHE II score (AUC: 0.811), SOFA score (AUC: 0.759), and sum of APACHE II and SOFA score (AUC: 0.815) (all p < 0.001). Interpretation: We successfully develop an accurate prediction nomogram for ICU mortality in severe Covid-19 population, which serves to recognize the patients with high risk of ICU mortality and to facilitate stratification management. Funding Statement: The authors received no funding support to undertake this study. Declaration of Interests: All authors declare no competing interests. Ethics Approval Statement: This study was exempt from ethic review and written informed consent was also waived by the Research Ethics Board of Wuhan Jinyintan Hospital due to its nature of retrospective design.