Development and Validation of a Nomogram Predictive Model for Massive Ascites After Hepatectomy in Patients with Primary Hepatocellular Carcinoma

Objective: To develop and validate a nomogram for predicting massive ascites after hepatectomy in hepatocellular carcinoma (HCC) patients. Methods: A retrospective study of 232 HCC patients undergoing hepatectomy (Feb 2021–Jul 2025) was conducted. Patients were grouped by postoperative ascites status (massive, n=66; non-massive, n=166). Predictors were screened via univariate and multivariate logistic regression. A nomogram was built and internally validated using 1000 bootstrap samples. Performance was assessed via ROC analysis, calibration, and decision curve analysis (DCA)，Clinical Impact Curve（CIC). Results: Multivariate analysis identified four independent predictors: platelet count (OR=0.985), AST (OR=1.027), portal hypertension (OR=5.288), and operative time (OR=5.011). The nomogram achieved an AUC of 0.837 (95% CI: 0.781–0.892) with good calibration (H-L test, P=0.860). DCA showed clinical net benefit across thresholds [0.00–0.71] and [0.86–0.93]and the clinical impact curve showing good concordance at risk thresholds above 0.4. Conclusions: The nomogram accurately predicts massive ascites risk using four perioperative variables and demonstrates strong clinical utility for individualized management.