Analysis of risk factors and construction of predictive model for post-endoscopic retrograde cholangiopancreatography pancreatitis

被引:1
|
作者
Zhu, Ping [1 ]
机构
[1] First Peoples Hosp Linping Dist, Dept Gastroenterol, Hangzhou 311100, Zhejiang Provin, Peoples R China
关键词
Endoscopic retrograde cholangiopancreatography; Pancreatitis; Risk factors; Prediction model; Nomogram;
D O I
10.12669/pjms.39.6.7972
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objective: To explore the risk factors of post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) and to establish a predictive model. Methods: This was a retrospective observational study. Patients diagnosed with calculous cholangitis and treated with ERCP (n=998) in The First People's Hospital of Linping District from January 2014 to September 2022 were included. Risk factors of PEP were identified using univariate and multivariate logistic regression, and a nomograph prediction model was established based on the identified independent risk factors. Results: PEP occurred in 52 patients (5.2%). Logistic regression analysis showed that common bile duct diameter, history of PEP, operation time, intubation frequency, pancreatic ducts visualization, and Sphincter of Oddi dysfunction (SOD) were independent risk factors for inducing PEP (P<0.05). The calibration curve showed that the predicted probability of occurrence of the nomograph model was consistent with the actual probability of occurrence. The C-index value calculated by the Bootstrap method was 0.966, suggesting the nomograph prediction model has a good discrimination ability. The AUC of the nomograph prediction model ROC curve was 0.966 (95% CI: 0.857-0.941), suggesting good prediction efficiency, and the decision analysis curve shows a high value. Conclusions: Independent risk factors for PEP are large diameter of common bile duct, history of pancreatitis, long operation time, high intubation frequency, pancreatic ducts visualization, and SOD. The nomogram prediction model based on the above independent risk factors has good prediction ability.
引用
收藏
页码:1642 / 1646
页数:5
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