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David Fernando Duque Ropero

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Open access Jul 2026

Preoperative artificial intelligence-based risk model for surgical reintervention after microsurgical free flap reconstruction.

BACKGROUND Flap-related vascular complications requiring surgical reintervention remain a source of morbidity after microsurgical free flap reconstruction and preoperative risk estimation relies on clinical judgement. Therefore, we developed and internally validated a strictly preoperative multivariable model for this outcome. METHODS A retrospective cohort of 650 consecutive adults at two high-volume referral centres (649 analysable) was analysed. The primary outcome was unplanned re-exploration within 30 days for arterial, venous, mixed thrombosis, or clinically significant vasospasm. Nineteen preoperative predictors were considered; intraoperative and surgeon variables were excluded. Least absolute shrinkage and selection operator (LASSO), random forest, and XGBoost were fitted on a 70% training partition and evaluated on a 30% test set. Performance was assessed using discrimination (AUC), calibration (intercept, slope, ICI, and E/O), and Brier score. Reporting followed TRIPOD; risk of bias used the four-domain PROBAST. RESULTS Event rate was 17.1% (111/649). XGBoost achieved the highest discrimination (AUC 0.84; 95% CI 0.74-0.92) and relatively better calibration (intercept 0.02, slope 0.87, ICI 0.039, E/O 0.89). Random forest showed comparable discrimination (AUC 0.82; 0.71-0.90) but poorer calibration (slope 1.33). LASSO demonstrated the lowest discrimination (AUC 0.79; 0.69-0.88). Prior oncologic history, surgical indication, and flap composition were influential predictors. A decile table from XGBoost showed a monotonic gradient, with events rising from ≤10% in lower deciles to 80% (95% CI 58-92) in the top decile. CONCLUSIONS XGBoost is retained as the principal model based on combined superiority in discrimination and calibration, with random forest as a robust comparator. The model is not decision-ready, and prospective external validation with recalibration is required before clinical adoption. LAY SUMMARY Using 649 analysable free flap reconstructions, we developed preoperative models to predict unplanned surgical reintervention for flap-related vascular complications within 30 days. XGBoost performed the best (AUC 0.84), supporting risk stratification before surgery, but prospective external validation is needed before clinical use.

Luis Arturo Molina Laguna, A. Porras-Ramírez, Giovanni Montealegre et al. · 0 citations