Predicting the risk of intensive care unit admission in patients with COVID-19 presenting in the emergency room: Development and evaluation of the CROSS score

Background Existing risk evaluation tools underperform in predicting intensive care unit (ICU) admission for patients with the Coronavirus Disease 2019 (COVID-19). This study aimed to develop and evaluate an accurate and calculator-free clinical tool for predicting ICU admission at emergency room (ER) presentation. Methods Data from patients with COVID-19 in a nationwide German cohort (March 2020-January 2023) were analyzed. Candidate predictors were selected based on literature and clinical expertise. A risk score, predicting ICU admission within seven days of ER presentation, was developed using elastic net logistic regression on a northern German cohort (derivation cohort), evaluated on a southern German cohort (evaluation cohort) and externally validated on a Colombian cohort. Performance was evaluated through discrimination, calibration, and clinical utility against existing tools. Results ICU admission rates within seven days were 30.8% (derivation cohort, n=1295, median age 60, 38.1% female), 28.1% (evaluation cohort, n=1123, median age 58, 36.9% female), and 30.3% (Colombian cohort, n=780, median age 57, 38.8% female). The 11-point CROSS score, based on Confusion, Respiratory rate, Oxygen Saturation (with or without concurrent supplemental oxygen), and oxygen Supplementation, demonstrated good discrimination (area under the curve (AUC): 0.77 in the evaluation cohort; 0.69 in the Colombian cohort), good calibration, and superior clinical utility compared to existing tools. Mortality-predicting tools performed poorly in predicting ICU admission risk for patients with COVID-19. Conclusions The calculator-free CROSS score effectively predicts ICU admission for patients with COVID-19 in the ER. Further studies are needed to assess its generalizability in other settings. Mortality-predicting tools are not recommended for ICU admission prediction.