Development and external validation of a model for post-endoscopic retrograde cholangiopancreatography pancreatitis

IF 4.6 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

iScience Pub Date : 2025-05-02 DOI:10.1016/j.isci.2025.112570

Gang Wang , Qikai Sun , Hai Zhu , Song Qiao , Peng Xu , Xiangyu He , Xiangkun He , Xiaosi Hu , Mingming Song , Qiuyan Zhang , Zhenyu Feng , Yue Chen , Yue Gao , Zhiyuan Jin , Wen Li , Haizheng Tang , Chaoqun Yan , Yajun Wei , Shibo Xu , Gang Hu , Cheng Wang

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引用次数: 0

Abstract

Post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) is a common complication in patients undergoing ERCP for choledocholithiasis, yet effective predictive models are lacking. This study included 2,247 patients who underwent ERCP for complete stone removal at the First Affiliated Hospital of USTC from January 2015 to January 2023. Six machine learning algorithms were utilized, incorporating 25 clinical parameters, to develop a predictive model for PEP risk. The random forest (RF) algorithm achieved the highest accuracy, with an area under the receiver operating characteristic curve (AUC) of 0.947 in the internal dataset. Key risk factors for PEP identified include difficult cannulation, a history of pancreatitis, smaller common bile duct diameter, and female gender. Validation with datasets from 12 external centers showed AUC values ranging from 0.576 to 0.913, with an average of 0.768. An interactive R Shiny web application was also developed, offering a user-friendly tool for predicting PEP risk and enabling individualized management.

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内镜后逆行胆管胰造影术胰腺炎模型的建立和外部验证

内镜下逆行胰胆管造影（ERCP）后胰腺炎（PEP）是胆总管结石患者行ERCP后常见的并发症，但目前缺乏有效的预测模型。本研究纳入2015年1月至2023年1月在中国科大第一附属医院行ERCP全结石取出术的2247例患者。利用6种机器学习算法，结合25个临床参数，建立PEP风险的预测模型。随机森林（random forest， RF）算法的准确率最高，在内部数据集中的接收者工作特征曲线（receiver operating characteristic curve， AUC）下面积为0.947。确定PEP的主要危险因素包括插管困难、胰腺炎病史、胆总管直径较小和女性。对12个外部中心的数据集进行验证，AUC值范围为0.576 ~ 0.913，平均值为0.768。还开发了一个交互式R Shiny web应用程序，提供了一个用户友好的工具来预测PEP风险并实现个性化管理。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

iScience Multidisciplinary-Multidisciplinary

CiteScore

7.20

自引率

1.70%

发文量

1972

审稿时长

6 weeks

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