Development and validation of a dynamic prediction tool for post-endo-scopic retrograde cholangiopancreatography early biliary tract infection in patients with choledocholithiasis
10.12138/j.issn.1671-9638.20245176
- VernacularTitle:胆总管结石患者ERCP术后早期胆道感染的动态预测工具开发及验证
- Author:
Peng LI
1
;
Chao LIANG
;
Jia-Feng YAN
;
Chun-Hui GAO
;
Zhi-Jie MA
;
Zhan-Tao XIE
;
Ming-Jie SUN
Author Information
1. 河南省人民医院医院感染管理办公室,河南 郑州 450001
- Keywords:
choledocholithiasis;
endoscopic retrograde cholangiopancreatography;
biliary tract infection;
directed acyclic graph;
prediction
- From:
Chinese Journal of Infection Control
2024;23(6):692-699
- CountryChina
- Language:Chinese
-
Abstract:
Objective To develop a prediction tool for post-endoscopic retrograde cholangiopancreatography(ER-CP)early biliary tract infection(PEEBI)in patients with choledocholithiasis,and assist clinical decision-making be-fore ERCP and early personalized intervention after ERCP.Methods An observational bidirectional cohort study was adopted to select inpatients with choledocholithiasis who underwent ERCP in a hospital.Directed acyclic graph(DAGs)and the least absolute shrinkage and selection operator(LASSO)were used to predict PEEBI based on lo-gistic regression,and the models were compared and validated internally and externally.Results From January 1,2020 to September 30,2023,a total of 2 121 patients with choledocholithiasis underwent ERCP were enrolled,of whom 77(3.6％)developed PEEBI,mostly in the first 2 days after surgery(66.2％).The major influencing fac-tors for PEEBI were non-iatrogenic patient-related factors,namely diabetes mellitus(OR=2.43,95％CI:1.14-4.85),bile duct malignancy(OR=3.95,95％CI:1.74-8.31)and duodenal papillary diverticulum(OR=4.39,95％CI:1.86-9.52).Compared with the LASSO model,the DAGs model showed higher ability(3.0％)in com-prehensive discrimination(P=0.007),as well as good differentiation performance(D=0.133,P=0.894)and cal-ibration performance(x2=5.499,P=0.703)in external validation.Conclusion The DAGs model constructed in this study has good predictive performance.With the help of this tool,targeted early preventive measures in clinical practice can be taken to reduce the occurrence of PEEBI.
