Proposed intensive care unit triage models lack predictive validity for hospital mortality to deal with catastrophes: insights from a cohort study.

OBJECTIVE: To evaluate the predictive validity of the White and Associação de Medicina Intensiva Brasileira (AMIB) criteria in predicting hospital mortality among critically ill COVID-19 patients in Brazil. METHODS: We conducted a retrospective cohort study using data from 992 mechanically ventilated COVID-19 patients admitted to a large Brazilian academic hospital, during the first pandemic wave. We applied White and AMIB triage models to this cohort and assessed their performance in predicting hospital mortality. We assessed discrimination AUROC, calibration and overall accuracy (Brier score). Decision curve analysis was used to evaluate clinical utility across varying risk thresholds. RESULTS: Out of 992 eligible patients, the hospital mortality was 58%. The White model demonstrated moderate discrimination (AUROC 0.73; 95%CI 0.70 - 0.76), fair overall accuracy (Brier = 0.205) and adequate calibration. The AMIB model had poor discrimination (AUROC 0.67; 95%CI 0.64 - 0.70) and overall accuracy (Brier = 0.222), with poor calibration. Neither model demonstrated significant net benefit for decision thresholds above 80% risk of death. CONCLUSIONS: The White and AMIB triage models showed suboptimal performance in predicting hospital mortality in this cohort and were not effective standalone tools for intensive care unit triage, particularly for patients at the extremes of illness severity. These findings underscore the need for validation of triage tools before their implementation.