Development and external validation of a preoperative prediction model for in-hospital major adverse cardiovascular events after hip fracture surgery in older adults: a retrospective two-center study

Older adults with hip fracture are vulnerable to postoperative major adverse cardiovascular events (MACE) during hospitalization. However, early risk stratification remains difficult because existing assessments may require complex or late-available information. A simple model based on variables routinely available before surgery may support perioperative decision-making. We conducted a retrospective two-center cohort study of patients ≥ 60 years who underwent surgery for traumatic hip fracture at 2 hospitals in China. The development cohort included 935 patients treated between January 2024 and December 2025, and the external validation cohort included 168 patients treated between January 2020 and December 2025. Candidate preoperative predictors were screened using penalized regression. Six candidate prediction models were developed and compared using the same preprocessing pipeline. The final model was calibrated using Platt scaling. Model performance was assessed in an internal test set and an external validation cohort. In the development cohort, 122 of 935 patients developed postoperative in-hospital MACE. The final model was a Platt-calibrated logistic regression model including age, baseline electrocardiographic abnormality, chronic heart failure, serum potassium, albumin, and hemoglobin. In the internal test set, the model had an area under the receiver operating characteristic curve of 0.814, with a 95% CI of 0.748–0.876, and a Brier score of 0.102. At the prespecified threshold of 0.147, sensitivity was 0.710 and specificity was 0.754. In the external validation cohort, the area under the receiver operating characteristic curve was 0.760, with a 95% CI of 0.657–0.849. The Brier score was 0.141, sensitivity was 0.788, specificity was 0.630, and negative predictive value was 0.924. A simple preoperative logistic regression model based on routinely available clinical variables showed moderate discrimination in internal testing and provided preliminary external validation evidence for predicting postoperative in-hospital MACE after hip fracture surgery in older adults. The model may support early perioperative risk stratification and postoperative surveillance, although prospective multicenter validation and recalibration are needed before wider clinical use.