METHODS: This retrospective and multinational cohort study included all adult transferred injury patients from Korea, Malaysia, Vietnam, and Taiwan between 2016 and 2018. The outcome of interest was a death in the emergency department (ED) after the patients' ED visit. Using these results, we developed the interpretable field triage score with the Korea registry using an interpretable machine learning framework and validated the score externally. The performance of each country's score was assessed using the area under the receiver operating characteristic curve (AUROC). Furthermore, a website for real-world application was developed using R Shiny.

FINDINGS: The study population included 26,294, 9404, 673 and 826 transferred injury patients between 2016 and 2018 from Korea, Malaysia, Vietnam, and Taiwan, respectively. The corresponding rates of a death in the ED were 0.30%, 0.60%, 4.0%, and 4.6% respectively. Age and vital sign were found to be the significant variables for predicting mortality. External validation showed the accuracy of the model with an AUROC of 0.756-0.850.

INTERPRETATION: The Grade for Interpretable Field Triage (GIFT) score is an interpretable and practical tool to predict mortality in field triage for trauma.

METHODS: Patient and tumor characteristics as well as surgical outcomes from 11 international centers were recorded. All tumors were retrospectively assigned an Orbital Resection by Intranasal Technique (ORBIT) class and stratified based on surgical approach as either exclusively endoscopic or combined (endoscopic and open). Outcomes based on approach were compared using chi-squared or Fisher's exact tests. The Cochrane-Armitage test for trend was used to analyze outcomes by class.