Abstract
BACKGROUND: Large common bile duct stones (CBDSs) often require endoscopic papillary large balloon dilation (EPLBD) for removal. However, stone removal is sometimes insufficient when EPLBD is performed using conventional devices such as balloon catheters, basket catheters, and mechanical lithotripsy. Adjunctive electrohydraulic lithotripsy (EHL) is suggested to be useful for large CBDSs that cannot be removed by conventional approach. OBJECTIVES: The present study aimed to identify pre-procedural predictors for the need for EHL. DESIGN: A retrospective, single-center observational study. METHODS: Patients with CBDSs ⩾10 mm in diameter who underwent EPLBD or EHL between December 2017 and March 2025 were included. Clinical factors associated with the need for EHL in EPLBD to remove large CBDSs were analyzed by multivariate logistic regression. Receiver operating characteristic (ROC) curve analysis was performed to determine the predictive value of the independent risk factors. RESULTS: A total of 2881 patients underwent endoscopic retrograde cholangiopancreatography during the study period, 163 patients were included in this study. Among them, CBDS removal with EPLBD could be achieved with conventional devices in 123 patients, while 40 patients required EHL. Multivariate analysis suggested that independent risk factors for the need for EHL in EPLBD to remove CBDSs were a larger maximum bile duct diameter and a higher stone-to-distal bile duct diameter (SD) ratio. In ROC analysis, the SD ratio had the highest area under the curve of 0.82 (95% confidence interval, 0.75-0.89) with an optimal cut-off value of 1.17. The sensitivity, specificity, positive predictive value, and negative predictive value at this cutoff were 0.95, 0.51, 0.39, and 0.97, respectively. CONCLUSION: A higher SD ratio was shown to be a potential independent risk factor for the need for EHL in EPLBD for large CBDSs. Patients with a SD ratio ⩾1.17 may be more likely to require additional treatment. These findings are exploratory and require validation in future studies to confirm their robustness and support their generalizability.