Puntuación de disección ESD de Lyon: Un modelo de predicción preprocedimiento para el tiempo de quirófano en la...

Colorectal endoscopic submucosal dissection (ESD) is an effective curative technique for superficial colorectal lesions but remains technically demanding, with variable procedure times. This study aimed to develop and validate a pre-procedure predictive model for colorectal ESD duration in the era of traction-assisted strategies.

We retrospectively analyzed prospectively collected data from patients who underwent colorectal ESD at Edouard Herriot Hospital (Lyon, France). The derivation cohort included 423 cases (January-December 2024) and an independent temporal validation cohort 148 cases (January-May 2025). A generalized linear model with a gamma distribution and log-link function identified independent pre-procedural predictors of ESD duration. Variables were selected based on univariate significance and the Akaike Information Criterion. Model calibration and discrimination were assessed using R², mean absolute error, and classification accuracy at predefined thresholds (60, 90, 120 minutes). A point-based score (Lyon ESD Dissection Score, LEDs) and nomogram were derived from model coefficients.

Median procedure time in the derivation cohort was 50 minutes (IQR 30-90). Independent predictors of ESD duration included dissection speed of endoscopists, lesion location (flexures, appendix, cecum, ileocecal valve), predicted lesion size, and suspected fibrosis (all p < 0.05). The LEDs provides a direct estimation of the expected procedure time in minutes based on these variables, showing a strong correlation between predicted and observed durations (R² = 0.52). Classification accuracy was 76.1%, 82.2%, and 88.1% for thresholds of 60, 90, and 120 minutes, respectively. Validation confirmed good performance (R² = 0.48) with 91.8% accuracy for procedures ≥120 minutes.

This validated pre-procedure scoring system accurately predicts colorectal ESD duration, especially for longer procedures. It may facilitate scheduling, optimize resource use, and improve workflow in endoscopy units.