Adverse Events During Strategic Medical Evacuation of Combat Casualties: Risk Factors and Prediction Models

Strategic medical evacuation (SME) of critically injured blast casualties is challenged by prolonged transport, unstable physiological status, and resource limitations, increasing the risk of adverse events. Understanding predictors of in-transit deterioration may support safer evacuation planning and improve outcomes. This study aimed to identify risk factors for adverse events during SME and to develop clinically applicable prediction models.

A retrospective single-center cohort included 100 adult blast-injured casualties evacuated between 2022 and 2024 to a tertiary military hospital in Kyiv, Ukraine. Transport was performed by helicopter or by ground/rail critical care transport platforms. Demographic data, injury characteristics, physiological status, and adverse events during SME were analyzed. Logistic regression was used to identify independent predictors, and model performance was assessed using receiver operating characteristic (ROC) analysis.

Adverse events occurred in 8% of transports, including 3 deaths (2 in-transit, 1 within 24 hours post-arrival). Ground/rail evacuation was associated with a higher risk compared with aeromedical transport (OR 11.2; 95% CI 1.32-95.0; P = .027), while helicopter evacuation was protective (OR 0.09; 95% CI 0.01-0.79; P = .030). Each additional transport hour increased risk by 47% (OR 1.47; 95% CI 1.06-2.05; P = .022). In multivariable analysis, transport duration (b 0.46 ± 0.19; OR 1.58; P = .016) and body weight (b 0.058 ± 0.031; OR 1.06 per kg; P = .064) remained independent predictors (model χ2 = 11.32; P = .003). A 2-factor risk index (0.058 × weight [kg] + 0.46 × duration [h] - 4) showed AUC 0.82 (95% CI 0.73-0.89). A 7-factor model showed AUC 0.96 (95% CI 0.90-0.99), though its feasibility for rapid application may be limited.

Transport duration and body weight are key predictors of adverse events during SME of blast casualties. Reducing evacuation time and prioritizing aeromedical transport could help mitigate clinical risks. The 2-factor risk index supports rapid operational risk stratification and may assist transport modality selection in resource-limited settings, while further multicenter validation is required before broader implementation.