One‐Year Functional Outcomes Following Geriatric Hip Fracture: A Prospective Cohort Analysis - Wei Zheng; Qianying Cai; Changqing Zhang; Shengbao Chen; Kai Fu (Orthopaedic Surgery)
ABSTRACT Objective With the characteristics of population change, geriatric hip fracture is increasing, accompanied by high morbidity and mortality rates. However, limited research has thoroughly investigated the postsurgery functional outcomes of hip fractures in the elderly population. Methods This study included 993 patients who underwent hip fracture surgery, drawn from a prospective cohort in China. Demographic and clinical data were collected for all participants. The cohort was randomly divided into training and validation sets (8:2). Least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression analyses were employed to identify predictive factors for hip function at 12 months postoperatively. A nomogram was developed using R software and evaluated using concordance index (C‐indexes), area under the curve (AUC), decision curve analysis (DCA), and calibration curves. Results Patients were divided into training (n = 794) and validation set (n = 199). Eight independent predictive variables for the poor functional outcome (Harris Hip Score < 80) after hip fracture include age (odds ratio [OR], 1.08; 95% confidence interval [CI], 1.04–1.12), hypertension history (OR, 2.53; 95% CI, 1.50–4.23), fracture type (OR, 0.28; 95% CI, 0.17–0.48), blood transfusion (OR, 2.30; 95% CI, 1.35–3.94), baseline PARKER score (OR, 0.85; 95% CI, 0.75–0.97), adverse events occurred within 12 months postoperatively (OR, 5.49; 95% CI, 2.30–13.08), transfer to the rehabilitation institution (OR, 3.22; 95% CI, 1.51–6.88), and time from surgery to weight‐bearing (OR, 1.02; 95% CI, 1.01–1.03). The nomogram demonstrated excellent predictive ability in the training set (AUC = 0.853, [95% CI: 0.816–0.890]). Furthermore, according to the calibration curve, the model's prediction and actual observation were in good consistency, and the DCA curve demonstrated good clinical usefulness. Conclusions This study developed a personalized, predictive nomogram with eight risk factors for predicting 1‐year functional outcomes in geriatric patients with hip fractures. Our model facilitates the early identification of high‐risk patients and enables surgeons to implement timely preventive interventions.