Predictive modeling and risk factor analysis of common bile duct stones after laparoscopic cholecystectomy: implications for postoperative management in minimally invasive surgery

Minimally invasive surgery, particularly laparoscopic cholecystectomy, has become the standard treatment for gallbladder disease. However, postoperative recurrence of common bile duct stones (CBDS) remains a clinically significant complication that compromises recovery and long-term outcomes. This study aimed to identify independent risk factors associated with CBDS following laparoscopic cholecystectomy and to develop a visual predictive model for early warning and individualized postoperative management. We collected data from 891patients who underwent cholecystectomy at Affiliated Hospital Group of Guangdong Medical University Panyu He Xian Memorial Hospital (Panyu District, Guangzhou) between September 2021and September 2024, Patients were followed for 12 months postoperatively, and 80 developed recurrent CBD stones. Demographic characteristics (age, history of liver fluke infection) and perioperative laboratory indicators (C-reactive protein [CRP], alanine aminotransferase [ALT], total bilirubin [TB], and common bile duct diameter) were compared using SPSS 27.0. Univariate and multivariate logistic regression analyses, combined with LASSO regression, were employed to identify independent predictors, which were incorporated into a nomogram model. Model performance was assessed by discrimination (AUC), calibration (calibration curve and Hosmer–Lem show test), and clinical utility (decision curve analysis), with internal validation via bootstrapping (1,000 repetitions). Multivariate analysis identified six independent predictors of CBD stone recurrence: older age (OR = 1.03 per year, 95% CI: 1.01–1.07, P = 0.019), elevated CRP (OR = 1.03 per mg/L, 95% CI: 1.00–1.07, P = 0.023), higher ALT (OR = 1.02 per U/L, 95% CI: 1.01–1.02, P < 0.001), increased TB (OR = 1.02 per µmol/L, 95% CI: 0.99–1.05, P = 0.14, considered clinically relevant despite marginal statistical significance), larger CBD diameter (OR = 1.60 per mm, 95% CI: 1.27–2.01, P < 0.001), and positive liver fluke infection history (OR = 2.09, 95% CI: 0.85–5.16, P = 0.108, retained due to strong epidemiological and biological plausibility). The final nomogram demonstrated excellent discrimination with an AUC of 0.835 (95% CI: 0.773–0.896) and good calibration (mean absolute error = 0.033). Internal validation confirmed robustness (bootstrap-corrected C-index = 0.835). Decision curve analysis indicated that the model provided superior net clinical benefit compared to treat-all or treat-none strategies across a wide range of risk thresholds (10%–30%). Our predictive model integrates key perioperative factors—including age, CRP, ALT, TB, common bile duct diameter and liver fluke infection—to accurately identify patients at high risk of CBDS recurrence after laparoscopic cholecystectomy. This nomogram enables personalized postoperative surveillance and early intervention in minimally invasive biliary surgery, ultimately supporting enhanced recovery and precision surgical care.

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Publication Details

Journal
BMC Surgery
Published
2026-03-27
DOI
https://doi.org/10.1186/s12893-026-03699-1
Primary Topic
Gallbladder and Bile Duct Disorders
Type
article
Field-Weighted Citation Impact
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article

Predictive modeling and risk factor analysis of common bile duct stones after laparoscopic cholecystectomy: implications for postoperative management in minimally invasive surgery

Song Wu, Yonghui Peng, Duhui Gong, Wenjie Zhang
BMC Surgery
Gallbladder and Bile Duct Disorders
article

Predictive modeling and risk factor analysis of common bile duct stones after laparoscopic cholecystectomy: implications for postoperative management in minimally invasive surgery

Song Wu, Yonghui Peng, Duhui Gong, Wenjie Zhang
article en

Abstract

Minimally invasive surgery, particularly laparoscopic cholecystectomy, has become the standard treatment for gallbladder disease. However, postoperative recurrence of common bile duct stones (CBDS) remains a clinically significant complication that compromises recovery and long-term outcomes. This study aimed to identify independent risk factors associated with CBDS following laparoscopic cholecystectomy and to develop a visual predictive model for early warning and individualized postoperative management. We collected data from 891patients who underwent cholecystectomy at Affiliated Hospital Group of Guangdong Medical University Panyu He Xian Memorial Hospital (Panyu District, Guangzhou) between September 2021and September 2024, Patients were followed for 12 months postoperatively, and 80 developed recurrent CBD stones. Demographic characteristics (age, history of liver fluke infection) and perioperative laboratory indicators (C-reactive protein [CRP], alanine aminotransferase [ALT], total bilirubin [TB], and common bile duct diameter) were compared using SPSS 27.0. Univariate and multivariate logistic regression analyses, combined with LASSO regression, were employed to identify independent predictors, which were incorporated into a nomogram model. Model performance was assessed by discrimination (AUC), calibration (calibration curve and Hosmer–Lem show test), and clinical utility (decision curve analysis), with internal validation via bootstrapping (1,000 repetitions). Multivariate analysis identified six independent predictors of CBD stone recurrence: older age (OR = 1.03 per year, 95% CI: 1.01–1.07, P = 0.019), elevated CRP (OR = 1.03 per mg/L, 95% CI: 1.00–1.07, P = 0.023), higher ALT (OR = 1.02 per U/L, 95% CI: 1.01–1.02, P < 0.001), increased TB (OR = 1.02 per µmol/L, 95% CI: 0.99–1.05, P = 0.14, considered clinically relevant despite marginal statistical significance), larger CBD diameter (OR = 1.60 per mm, 95% CI: 1.27–2.01, P < 0.001), and positive liver fluke infection history (OR = 2.09, 95% CI: 0.85–5.16, P = 0.108, retained due to strong epidemiological and biological plausibility). The final nomogram demonstrated excellent discrimination with an AUC of 0.835 (95% CI: 0.773–0.896) and good calibration (mean absolute error = 0.033). Internal validation confirmed robustness (bootstrap-corrected C-index = 0.835). Decision curve analysis indicated that the model provided superior net clinical benefit compared to treat-all or treat-none strategies across a wide range of risk thresholds (10%–30%). Our predictive model integrates key perioperative factors—including age, CRP, ALT, TB, common bile duct diameter and liver fluke infection—to accurately identify patients at high risk of CBDS recurrence after laparoscopic cholecystectomy. This nomogram enables personalized postoperative surveillance and early intervention in minimally invasive biliary surgery, ultimately supporting enhanced recovery and precision surgical care.

BMC Surgery
Guangdong Medical College (CN), Guangzhou Medical University (CN)
Peace, Justice and strong institutions, Reduced inequalities
Openalex Percentile: Top 6%
Gallbladder and Bile Duct Disorders
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