Construction and validation of a nomogram prediction model for factors affecting hip functional recovery after PFNA internal fixation of intertrochanteric femur fractures in the elderly

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A nomogram prediction model was developed with the aim of identifying and analyzing which independent risk factors affect the recovery of hip function in elderly patients with intertrochanteric femur fractures after undergoing proximal femoral anti-rotation intramedullary nailing (PFNA) internal fixation. We collected detailed data on elderly patients with intertrochanteric femur fractures from January 2018 to December 2022 in a tertiary hospital in China. By applying univariate and multivariate logistic regression analysis, we systematically screened and identified the independent risk factors affecting the recovery of hip function after PFNA internal fixation. Based on these risk factors, we further constructed a corresponding nomogram prediction model. In order to comprehensively evaluate the predictive performance of the model, we not only plotted the receiver operating characteristic curve and calculated the area under the curve, but also produced the calibration curve and decision curve. Of the total 646 patients included, 510 patients had good hip function recovery and were categorized as the excellent hip function group, while the other 136 patients had poor hip function recovery and were categorized as the poor hip function group. After rigorous unifactorial and multifactorial logistic regression analyses, we identified 5 key risk factors, which were: fracture instability, posterolateral wall type III, posterolateral wall thickness less than or equal to 2 cm, cusp distance >25 mm, and delayed postoperative weight-bearing. Together, these factors constitute the main risk factors affecting the recovery of hip function after PFNA internal fixation of intertrochanteric femur fractures in the elderly. In this study, a nomogram prediction model for the recovery of hip function after PFNA internal fixation of intertrochanteric femur fractures in the elderly was successfully constructed, and the model demonstrated good prediction accuracy. This not only provides a powerful tool for orthopedic surgeons so that they can identify and intervene in advance with risk factors that may affect patients’ hip functional recovery, but also provides a scientific basis for developing more precise and personalized treatment strategies.