ArticleSurgical endoscopy2025
Machine learning-derived predictive model for post-ERCP pancreatitis in patients with common bile duct stones: a retrospective multicenter study.
Article in Surgical endoscopy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Advances in Artificial Intelligence for Gastrointestinal Endoscopy: 2026 Update.Diagnostics (Basel, Switzerland) · 2026Review
- Predictive factors and nomogram for post-endoscopic retrograde cholangiopancreatography pancreatitis.BMC gastroenterology · 2026Article
- AI-Based Prediction of Post-ERCP Pancreatitis: A Comparative Study Using Tabular, Image, and Multimodal Data.Diagnostics (Basel, Switzerland) · 2026Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCommon bile duct stones (CBDS) are the primary indication for endoscopic retrograde cholangiopancreatography (ERCP), yet post-ERCP pancreatitis (PEP) remains a significant complication due to its multifactorial etiology. This study aimed to identify core predictors and develop an optimized predictive model for PEP.
methodsWe retrospectively enrolled patients who underwent ERCP in three centers between March 2019 and March 2024. Potential predictors and their importance were evaluated with four machine learning (ML) algorithms. Predictive models were developed using logistic regression and assessed for discrimination, calibration, and clinical utility.
resultsA total of 1758 patients were included in the training (n = 917), testing (n = 392), validation 1 (n = 366), and validation 2 (n = 83) cohorts. The incidences of PEP were 6.7%, 6.6%, 10.1%, and 12.0%, respectively, with no significant difference among them (p = 0.063). Using ML, eight critical predictors were identified: age, direct bilirubin, serum calcium, γGT, cannulation attempts, transpancreatic precut, pancreatic guidewire passage, and endoscopic papillary balloon dilation (EPBD) duration. Model 3, incorporating serum calcium (OR: 2.50, p = 0.002), transpancreatic precut (OR: 4.61, p < 0.001), pancreatic guidewire passage (OR: 3.62, p < 0.001), and EPBD duration (OR: 2.25, p = 0.009), exhibited the highest AUC (0.845) and superior sensitivity (83.2%). Internal and external validations confirmed robustness and generalizability of the model, demonstrating excellent predictive performance and clinical utility.
conclusionWe established and validated an optimized predictive model for PEP using four key predictors, enhancing early identification and intervention after ERCP for patients with CBDS.
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