Construction And Validation Of A Clinical Prediction Model For Early Complications After Hip Arthroplasty

Objective:Artificial hip arthroplasty is the most effective method for the treatment of end-stage hip diseases.The occurrence of postoperative complications significantly affects the surgical effect and postoperative functional recovery,increases medical costs,and even leads to surgical failure,disability and death.This study aims to identify preoperative and intraoperative risk factors associated with early complications after hip arthroplasty via a clinical prediction model to predict the likelihood of complications within 30 days after surgery.Methods:The baseline data of all patients who underwent hip arthroplasty from January 2016 to June 2022 were retrospectively analyzed.The patients were divided into non-complication group and complication group according to whether the presence of complications.Least absolute shrinkage and selection operator(Lasso)regression,univariate analysis and multivariate binary logistic regression were used to screen the best predictors of the model,and finally the nomogram model was established by R software using multivariate regression analysis results.The consistency index(C-index),receiver operating characteristic(ROC)curve,decision curve analysis(DCA)and calibration curve were used to evaluate the clinical prediction model and internally validate.Results:A total of 231 patients were included in this study for evaluation.Multivariate Logistic regression analysis showed that alanine aminotransferase,serum albumin,operation time and osteoporosis were independent risk factors for early complications after hip replacement.The C-index of the clinical prediction model was 0.736(95%CI:0.659-0.814),and the area under curve(AUC)was 0.736.Nevertheless the adjusted C-index was 0.720,suggesting that the nomogram model had excellent adequacy and accuracy.The results showed that the predicted value was in good agreement with the actual value.The decision curve analysis(DCA)results indicated that the net benefit rate of the prediction model was greater than zero when the risk threshold was set between 0%and 75%.C onclusion:A nomogram model was developed based on the preoperative and intraoperative factors related to early complications after artificial hip arthroplasty.Clinically,the individualized prediction model can be used to determine the possibility of complications after hip replacement among high-risk patients.