ArticleHernia : the journal of hernias and abdominal wall surgery2026
External validation of the IHXGboost-P model to predict incisional hernia after midline laparotomy.
Article in Hernia : the journal of hernias and abdominal wall surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundIncisional hernia (IH) is a significant complication that occurs after midline laparotomy and is associated with high morbidity and economic impacts. A fundamental goal of preventing IH is to determine which patients are considered low- or high-risk, as modifications in prevention techniques have been justified in high-risk patients.
aimof this study was to externally validate the IHXGBoost-P model to assess its accuracy, generalizability, and clinical applicability in an independent cohort.
methodsA prospective cohort study was conducted in a tertiary hospital in Mexico (March 2021-December 2022) to externally validate the IHXGBoost-P model. Patients older than 18 years who underwent midline laparotomy and have a minimum follow-up of 24 months were included. The performance of the model was evaluated via area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, precision, specificity and calibration metrics.
resultsOf the 438 patients analyzed, 62 (14.1%) developed IH. The model demonstrated good discriminative capacity (Accuracy: 0.94 ± 0.015) and calibration (Brier score: 0.051). Key predictors included the risk of surgical site infection (odds ratio (OR): 3.01, 95% CI: 2.32-3.91), previous surgery, and body mass index (BMI). The specificity (0.97 ± 0.013) was determined to be high and useful for identifying lowrisk patients.
conclusionsThe IHXGBoost-P model is a reliable tool for predicting the risk of IH, with robust performance being observed in external validation. Its integration into clinical practice through a web application could optimize surgical decision-making to prevent IH.
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