• Shaochuan Chen, Jiale Yang, Xuezhi Shi, Anwei Liu, Guodong Lin, and Huasheng Tong.
• Department of Emergency Medicine, Huiyang Sanhe Hospital, Huizhou, China.
• Intern Emerg Med. 2025 Jan 28.

AbstractMulti-trauma presents significant challenges due to the complexity of injuries and high mortality rates. Early identification and intervention are crucial for improving outcomes in these critically injured patients. This retrospective study analyzed clinical data from multi-trauma patients admitted to the emergency department of Huiyang Sanhe Hospital between January 10, 2020, and September 30, 2022. Univariate and multivariate logistic regression analyses were conducted to identify independent predictors of hospital mortality. A prediction model was developed based on these prognostic markers, visualized using a nomogram, and its discriminative ability and clinical benefit were evaluated. A total of 124 multi-trauma patients were included in the study, with a hospital mortality rate of 26.7%. Univariate and multivariate logistic regression analyses identified trauma-induced coagulopathy (TIC) (OR 4.238, 95% CI 1.46-12.28), blood urea nitrogen (BUN) (OR 1.397, 95% CI 1.09-1.78), and Glasgow Coma Scale (GCS) score (OR 0.720, 95% CI 0.61-0.85) as independent factors of hospital mortality. Therefore, a nomogram incorporating TIC, BUN, and GCS score was constructed and demonstrated excellent predictive performance and clinical impact (AUC 0.898, 95% CI 0.834-0.962). The nomogram developed in this study provided a practical tool for early prediction of hospital mortality in multi-trauma patients. By focusing on TIC, BUN, and GCS score, this model may facilitate rapid bedside assessment and timely intervention. However, further multicenter, prospective studies are required to validate its performance and applicability.© 2025. The Author(s).

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