Prediction model for prolonged length of stay in hip fracture patients

Abstract

Abstract Background The length of hospital stay in hip fracture patients is closely associated with medical costs, the burden of which is increasing in aging societies. Herein, we developed and validated models for predicting prolonged length of stay in hip fracture patients to support efficient care in these patients. Methods This was a retrospective analysis of all patients undergoing hip fracture from January 2021 to December 2021. Univariate and multivariate logistic regression analyses were used to evaluate the association between risk factors and delayed discharge after hip fracture. Finally, the risk factors obtained from the multivariate regression analysis were used to establish the nomogram model. The validation of the nomogram was assessed by the concordance index (C-index), the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and calibration curves. the STROBE checklist was used as the reporting guideline. Results A total of 1259 patients were included in the present study for evaluation. Multivariate logistic regression analysis demonstrated that CCI, Preoperative waiting time, Anemia, Hypoalbuminemia and Arteriosclerosis of lower limbs were independent risk factors for delayed discharge after hip fracture. The C-index of this model was 0.82 (95% CI, 0.793–0.847). Internal validation proved the nomogram model’s adequacy and accuracy, and the results showed that the predicted value agreed well with the actual values. Conclusions Our prediction models may help policymakers in developing strategies for the optimal management of hip fracture patients with a focus on patients at a high risk of prolonged length of stay.