ArticlePediatric surgery international2026
Machine learning-based prediction model for risk factors associated with conversion to open surgery in pediatric laparoscopic radical resection of choledochal cysts.
Article in Pediatric surgery international, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Beyond scalar thresholds: leveraging medical vision foundation models for pediatric surgical risk stratification.Pediatric surgery international · 2026Article
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6 authors.
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Abstract
objectiveTo identify risk factors for conversion to open surgery during laparoscopic choledochal cyst excision in pediatric patients and develop a predictive model using machine learning.
methodsWe retrospectively analyzed 214 children who underwent laparoscopic excision between 2015 and 2023. Patients were classified into laparoscopic (n = 173) or conversion (n = 41) groups. Seven machine learning models were developed and evaluated using AUC and decision curve analysis (DCA). SHAP analysis identified top predictors, which were validated via multivariable logistic regression. A nomogram was constructed and internally validated for discrimination, calibration, and clinical utility.
resultsGBM performed best (AUC = 0.897) with the highest net benefit on DCA. SHAP highlighted age, cyst wall thickening (≥ 3 mm), obstructive jaundice, cyst diameter, ALT, and history of perforation. Multivariable analysis confirmed age (OR = 1.022, 95% CI 1.01–1.04; P = 0.004), cyst wall thickening (OR = 15.024, 95% CI 5.03–49.48; P < 0.001), and obstructive jaundice (OR = 10.933, 95% CI 2.76–49.28; P = 0.001) as independent predictors. The nomogram achieved a C-index of 0.843 (95% CI 0.814–0.872), showed good calibration (P = 0.318), and demonstrated consistent performance in cross-validation and DCA. The optimal age cutoff was 27.5 months.
conclusionAge > 27.5 months, cyst wall thickening, and obstructive jaundice are key predictors of conversion. The nomogram provides a clinically useful tool for preoperative risk stratification, pending external validation.
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