The Predictive Performance of Risk Scores for the Outcome of COVID-19 in a 2-Year Swiss Cohort

Abstract

Various scoring systems are available for COVID-19 risk stratification. This study aimed to validate their performance in predicting severe COVID-19 course in a large, heterogeneous Swiss cohort. Scores like the National Early Warning Score (NEWS), CURB-65, 4C mortality score (4C), Spanish Society of Infectious Diseases and Clinical Microbiology score (COVID-SEIMC), and COVID Intubation Risk Score (COVID-IRS) were assessed in patients hospitalized for COVID-19 in 2020 and 2021. Predictive accuracy for severe course (defined as all-cause in-hospital death or invasive mechanical ventilation (IMV)) was evaluated using receiver operating characteristic curves and the area under the curve (AUC). The new ‘COVID-COMBI’ score, combining parameters from the top two scores, was also validated. This study included 1,051 patients (mean age 65 years, 60% male), with 162 (15%) experiencing severe course. Among the established scores, 4C had the best accuracy for predicting severe course (AUC 0.76), followed by COVID-IRS (AUC 0.72). COVID-COMBI showed significantly higher accuracy than all established scores (AUC 0.79, p = 0.001). For predicting in-hospital death, 4C performed best (AUC 0.83), and, for IMV, COVID-IRS performed best (AUC 0.78). The 4C and COVID-IRS scores were robust predictors of severe COVID-19 course, while the new COVID-COMBI showed significantly improved accuracy but requires further validation.

Keywords

• COVID-19
• SARS-CoV-2
• outcome
• severe course
• in-hospital death
• ventilation