Predicting long-term clinical mortality of elderly patients with vertebral compression fractures

< 0.001). Calibration curves and decision curve analysis further validated the model's clinical utility. The XGB model's interpretability was enhanced using SHAP values, providing insights into the influence of individual features on mortality risk. In conclusion, we developed a novel risk-stratification model for predicting mortality for VCFs. Our model can also aid in stratifying patients, with high discriminative ability. The use of an explainable machine learning model can aid physicians in making individualized treatment decision in VCFs patients.