Construction And Effect Evaluation Of A Prediction Model For Delayed Graft Function After Renal Transplantation

Objective:To construct a predictive model for delayed graft function(DGF)after renal transplantation,and to explore its predictive value for clinical application.Methods : The data of 223 renal transplantation recipients in our center were retrospectively analyzed,and they were randomly divided into a modeling group(157cases)and a verification group(66 cases)according to the ratio of 7:3.The occurrence and risk factors of DGF after renal transplantation in the modeling group were analyzed,and the prediction model was established according to the results of multivariate logistic regression analysis,and the data was verified by the validation group.A nomogram of the DGF prediction model was drawn and the accuracy was compared using the area under the curve(AUC)of the receiver operating characteristic(ROC)curve.Results : Among 223 kidney transplant recipients,the incidence of DGF was 46.2%(103/223).The existence of donor’s diabetes history,recipient’s abdominal surgery history,donor’s terminal creatinine≥93umol/L and recipient’s body mass index(BMI)>24 were independent risk factors for DGF(P<0.05).The DGF prediction model equation is logit(delayed graft function)=-1.039+1.554×donor’s diabetes history(yes=1,no=0)+1.379×recipient’s abdominal surgery history(yes=1,no =0)+1.172×donor terminal creatinine(<93umol/L=0,≥93umol/L=1)+1.224×recipient body mass index(≤24=0,>24=1).The AUC of ROC in modeling group was 0.857(95%CI: 0.793-0.922,P<0.001),the sensitivity was 82.1%,the specificity was 76.9%,and the AUC in the validation group was 0.820(95%CI: 0.703-0.937,P<0.001),with the sensitivity was81.8%,the specificity was 72.4%.Conclusions:The prediction model,consisting of donor’s diabetes history,recipient’s abdominal surgery history,the body mass index of the recipient and donor’s terminal creatinine,may effectively predict the occurrence of DGF.