Prospective Study of an Explainable AI Tool to Support Biliopancreatic Limb Selection in One-Anastomosis Gastric Bypass
This prospective observational cohort study will develop and externally validate a human-supervised, explainable artificial-intelligence decision-support model for analysing factors associated with biliopancreatic limb length selection during one-anastomosis gastric bypass (OAGB). The study will record three prespecified factors: the percentage of the laparoscopic instrument segment J-I covered by visceral or omental fat (P\_JI = 100 × FI/JI), the measured total small-bowel length (TSBL), and the abdominal integral index (AII = (CD/AC) + (CG/EG) + (JI/FI)). The study will evaluate weight-loss effectiveness, nutritional and malabsorptive outcomes, bile/acid reflux, major complications, and technical feasibility. During model development, the AI system will not autonomously assign a BPL length. The operating bariatric surgeon will make the clinical decision, and the model will be evaluated for calibration, external validity, factor contribution, safety constraints, and abstention.
Adults aged 18 years or older at the time of consent. [+5]
Revisional, conversion, or non-primary gastric bypass surgery. [+6]