Development and internal validation of a prediction model for in-hospital mortality in trauma patients with high-energy pelvic fractures admitted to a single major trauma centre

Background: Pelvic fractures, although relatively uncommon, are associated with high economic burden, morbidity, and substantial mortality rates ranging from. While previous studies have identified risk factors for mortality in these patients, there is currently no available specific prediction model for these injuries that has undergone methods of model development and internal validation. This single-center study aims to develop and internally validate a prediction model for in-hospital mortality in major trauma patients with high-energy pelvic fractures. Methods: Data were sourced from a Level I adult Major Trauma Centre’s registry, including patients > = 15 years old with Injury Severity Score (ISS) > 12 and pelvic fractures from July 2010 – December 2022. In-hospital mortality was the outcome of interest. Model development utilized backward elimination for predictor selection into a multivariable logistic regression model, with internal validation via bootstrap methods. The model performance was assessed using Brier scaled score and discrimination measures (c-statistic of the receiver operating characteristic curve), and calibration (calibration plot). Results: Out of 1564 included patients, 118 were non-survivors (mortality rate 7.5%). The optimism-adjusted prediction model identified ISS ≥ 50 (OR 7.4), age ≥ 65 (OR 6.1), and severe head injury (OR 3.6) as strong predictors of mortality. Additional predictors with ORs between 2–3, were ISS 25–49, shock, patients directly transported from the scene of injury, and severe comorbidity. The model demonstrated good to excellent discrimination with an optimism-adjusted c-statistic of 0.88. Conclusions: The study developed and internally validated a prediction model for in-hospital mortality in major trauma patients with high-energy pelvic fractures, identifying key predictors. While optimism-adjusted odds from internal validation were attenuated, the findings remain comparable to broader literature. External validation in futures studies is recommended to assess the model’s transportability and broader clinical applicability.