Risk Factors Analysis And Prediction Model Construction Of Revision In Patients Undergoing Total Hip Arthroplasty

Objective: To explore the risk factors of revision in patients undergoing primary total hip arthroplasty(THA),and construct a prediction model based on the screening results.In order to provide a risk quantification tool that effectively reducing the incidence of revision of total hip arthroplasty(r THA)in the clinic,and achieve the goal of early identification and precise intervention of high-risk patients.Methods: The clinical data of patients undergoing THA or r THA admitted to the First Affiliated Hospital of Kunming Medical University from January 2018 to November 2022 were retrospectively collected.Based on the inclusion and exclusion criteria,310 cases were finally selected.According to whether the joint revision occurred,the patients were divided into a revision group(n=109)and a non-revision group(n=201).The data including body mass index(BMI),age,gender,ethnicity,bad habits,Harris score,insulin usage,underlying diseases,NRS2002 score,ASA classification,surgical procedures,operation duration,surgical approach,red blood cell(RBC),white blood cell(WBC),neutrophil percentage(NEUT%),platelets(PLT),hemoglobin(HGB),albumin(ALB),and prealbumin(PA),alanine aminotransferase(ALT),aspartate aminotransferase(AST),creatinine(CREA),uric acid(UA),C-reactive protein(CRP),procalcitonin(PCT),erythrocyte sedimentation rate(ESR),prothrombin time(PT),thrombin time(TT),activated partial thromboplastin time(APTT),international normalized ratio(INR),high-density lipoprotein cholesterol(HDL-C),low-density lipoprotein cholesterol(LDL-C),triglycerides(TG),total cholesterol(TC),fasting blood glucose(FBG)were compared between the two groups.Using SPSS 25.0 software to conduct univariate and multivariate binary logistic regression analysis to screen out independent risk factors for r THA,construct the preoperative and postoperative prediction models based on the results,and draw the receiver operating characteristic(ROC)curve to evaluate the predictive value of two models for the risk of r THA.Results: The results of multivariate binary logistic regression analysis showed that preoperative BMI(OR=0.83,95%CI: 0.76-0.91,p<0.001),ASA classification(OR=4.76,95%CI: 2.05-11.05,p<0.001),ALB(OR=1.08,95%CI: 1.01-1.16,p=0.027),FBG(OR=1.18,95%CI: 1.02-1.36,p=0.030),CRP(OR=1.01,95%CI:1.01-1.03,p=0.012),PCT(OR=1.18,95%CI: 1.01-1.38,p=0.045),and postoperative BMI(OR=0.75,95%CI: 0.67-0.84,p<0.001),ASA classification(OR=4.74,95%CI:1.81-12.45,p=0.002),ALB(OR=1.17,95%CI: 1.08-1.26,p<0.001),CRP(OR=1.03,95%CI: 1.02-1.04,p<0.001),FBG(OR=1.27,95%CI: 1.13-1.43,p<0.001)were independent risk factors for r THA.According to the regression coefficients of the above independent risk factors,the preoperative and postoperative prediction models of r THA were constructed respectively.The preoperative combined predictive factors(L)model expression was: L=1.56 × ASA grade + 0.08 × ALB + 0.02 × CRP + 0.16 ×FBG + 0.16×PCT-0.18×BMI,and the postoperative combined predictive factors(L)model expression: L=1.56×ASA grade +0.16 × ALB + 0.03 × CRP + 0.24 × FBG-0.29× BMI.In the preoperative prediction model,the area under the ROC curve(AUC)was 0.90,the sensitivity was 0.83,the specificity was 0.84,and the best cut-off value was 5.50.In the postoperative prediction model,the area under the ROC curve(AUC)was 0.87,The sensitivity was 0.86,the specificity was 0.74,and the best cut-off value was 5.00.The results indicated that both models had good predictive value for predicting the risk of r THA.Conclusions:(1)Preoperative BMI,ASA classification,ALB,CRP,FBG,and PCT were independent risk factors for the occurrence of r THA after primary THA.Based on the above indicators,a preoperative r THA prediction model was constructed;(2)Postoperative BMI,ASA classification,ALB,CRP and FBG were independent risk factors for the occurrence of r THA after primary THA.Based on the above indicators,a preoperative r THA prediction model was constructed;(3)In this study,the preoperative and postoperative r THA prediction models were constructed.The results showed that both models had good predictive value,and their sensitivity and specificity were greater than those of each single independent risk factor.