Scoring System Development and Validation for Prediction Choledocholithiasis before Open Cholecystectomy

Area of Science:

• Hepatobiliary Surgery
• Surgical Diagnostics
• Medical Informatics

Background:

• Accurate detection of asymptomatic common bile duct stones (CBDS) is crucial for precholecystectomy decision-making.
• Current preoperative diagnostic methods for CBDS often lack sufficient accuracy.

Purpose of the Study:

• To develop and validate a predictive scoring model for common bile duct stones (CBDS) prior to open cholecystectomy.

Main Methods:

• Retrospective collection of preoperative and intraoperative data from 313 patients.
• Development of a scoring model using univariate and multivariate regression analysis.
• Assessment of the model's predictive ability, accuracy, AUC, calibration, and clinical utility.

Main Results:

• Total bilirubin, alkaline phosphatase, and bile duct dilation identified as independent predictors of CBDS.
• The scoring model demonstrated strong discriminatory ability (AUC 94.3% derivation, 89.9% validation) and excellent accuracy (95.5%).
• Satisfactory calibration and clinical utility were observed in decision curve analysis.

Conclusions:

• The developed scoring model shows potential for accurately estimating the presence of choledocholithiasis in patients scheduled for elective open cholecystectomy.