Artificial femoral head replacement for femoral neck fracture in the elderly:validation of a risk prediction model for hip dysfunction

Abuduainijiang·Abulimiti; Alimu·Mamuti; Li Simi

doi:10.12307/2025.756

Abstract：BACKGROUND:Artificial femoral head replacement is one of the primary surgical methods for femoral neck fractures in the elderly patients.However,postoperative hip dysfunction remains a common and challenging issue. OBJECTIVE:To establish and validate a nomogram prediction model for early improvement of hip joint function in elderly patients undergoing artificial femoral head replacement for femoral neck fractures. METHODS:230 patients who underwent hip hemiarthroplasty for femoral neck fractures at The First People's Hospital of Kashi Prefecture from January 2022 to October 2023 were retrospectively selected.Relevant factors that could influence early postoperative hip function were collected,and hip function improvement was assessed at 6 months postoperatively using the Harris Hip Score.Patients were divided into two groups based on whether their postoperative hip function improvement was satisfactory.Preoperative,intraoperative,and postoperative factors were compared between the two groups.Potential factors were screened using LASSO regression,followed by multivariate logistic regression to establish a nomogram prediction model using R4.1.3 software,which was then internally validated. RESULTS AND CONCLUSION:(1)A total of 221 patients were included in the study,with an average Harris Hip Score of(82.07±8.28)at 6 months postoperatively.(2)LASSO regression identified four potential influencing factors.Multivariate logistic regression analysis revealed that age,body mass index,time from injury to surgery,and time postoperative weight-bearing were independent factors affecting early postoperative hip function(P＜0.05).(3)Based on the multivariate results,a nomogram model was established.The calibration curve indicated good agreement between the predicted and observed outcomes.Receiver operating characteristic curve analysis results showed that the area under the curve for predicting early postoperative hip dysfunction using the nomogram model was 0.870[95％CI(0.819,0.921)].(4)Early postoperative hip function improvement was influenced by age,body mass index,time from injury to surgery,and time to postoperative weight-bearing.The nomogram model developed in this study demonstrates high discrimination and accuracy in predicting early hip dysfunction following artificial femoral head replacement.