Establishment and validation of risk prediction model for postoperative intraperitoneal infection in pancreaticoduodenectomy patients
OBJECTIVE To establish a novel type of risk prediction model for postoperative intraperitoneal infection(IAI)in the patients undergoing pancreaticoduodenectomy(PD)so as to provide theoretical basis for clinical diag-nosis and treatment.METHODS The clinical data were collected from 243 patients who underwent PD in the Third Central Hospital of Tianjin from Jun 2016 to Jun 2022 and were retrospectively analyzed.The risk factors for postoperative IAI in the PD patients were screened out by means of LASSO regression analysis,logistic regression analysis was performed to establish the risk prediction model for the postoperative IAI.The performance of the model was evaluated by C-index,receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA).RESULTS Of the 243 patients who underwent PD,96 had postoperative IAI,with the in-fection rate 39.5％.LASSO regression analysis showed that the size of tumor,pancreatic fistula,biliary fistula,intraabdominal hemorrhage and serum creatinine(Scr)were the risk factors for postoperative IAI in the PD pa-tients(P＜0.05).C-index of the model was 0.779(95％CI:0.738-0.821),the area under ROC curve(AUC)was 0.778,showing excellent discrimination degree;the calibration curve indicated that there was a good consistency between the probability of prediction for risk and the actual probability of occurrence.DCA curve showed that the model had high application value.CONCLUSION The PD patients are at high risk of postoperative IAI.The novel model that is established based on LASSO combined with logistic regression analysis can predict the postoperative IAI more accurately.
PancreaticoduodenectomyIntraperitoneal infectionPostoperative infectionRisk factorNomogramPrediction model
NETL
NSTL
万方数据
维普
