Background: No validated model incorporates surgical parameters for complication risk in hepatocellular carcinoma (HCC) resection. We evaluated a novel Surgical Burden Score (SBS), integrating adjusted blood loss (aBL; mL/kg) and operative time (hours) via a Pythagorean formula, and developed an SBS-based model to predict complications. Methods: Patients undergoing curative-intent hepatectomy for HCC(2000-2023) were identified from an international database. SBS was calculated as SBS2=(operative time)2+(aBL)2. Outcomes were any and severe complications (Clavien-Dindo ≥ III). ROC curves and AUCs evaluated performance. A 3:1 training/testing split was used for model development, incorporating SBS plus clinical variables. Results: Among 801 patients, complications occurred in 39.1 %, and severe complications in 11.0 %. On multivariable analysis, operative time (HR:1.231; 95%CI:1.113-1.365; p < 0.001) and aBL (HR:1.021; 95%CI:1.002-1.041; p = 0.036) were independent predictors of any complications. SBS(median:6.07 [IQR:4.08-10.07]) outperformed its components (AUC:0.71vs0.67 for operative time and 0.69 for aBL). Stratified SBS groups demonstrated a dose-dependent increase in complications (p < 0.001). The SBS-based model achieved AUCs of 0.73 (training) and 0.76 (testing), outperforming existing models. An online calculator is available (https://makbn.shinyapps.io/SBS_shiny/). Conclusions: SBS, a Pythagorean-based metric combining operative time and aBL, accurately predicts complications. The SBS-based model offers strong predictive utility for risk stratification.
The surgical burden score: a novel continuous metric to predict postoperative complications after hepatectomy for hepatocellular carcinoma
Ruzzenente, Andrea;
2025-01-01
Abstract
Background: No validated model incorporates surgical parameters for complication risk in hepatocellular carcinoma (HCC) resection. We evaluated a novel Surgical Burden Score (SBS), integrating adjusted blood loss (aBL; mL/kg) and operative time (hours) via a Pythagorean formula, and developed an SBS-based model to predict complications. Methods: Patients undergoing curative-intent hepatectomy for HCC(2000-2023) were identified from an international database. SBS was calculated as SBS2=(operative time)2+(aBL)2. Outcomes were any and severe complications (Clavien-Dindo ≥ III). ROC curves and AUCs evaluated performance. A 3:1 training/testing split was used for model development, incorporating SBS plus clinical variables. Results: Among 801 patients, complications occurred in 39.1 %, and severe complications in 11.0 %. On multivariable analysis, operative time (HR:1.231; 95%CI:1.113-1.365; p < 0.001) and aBL (HR:1.021; 95%CI:1.002-1.041; p = 0.036) were independent predictors of any complications. SBS(median:6.07 [IQR:4.08-10.07]) outperformed its components (AUC:0.71vs0.67 for operative time and 0.69 for aBL). Stratified SBS groups demonstrated a dose-dependent increase in complications (p < 0.001). The SBS-based model achieved AUCs of 0.73 (training) and 0.76 (testing), outperforming existing models. An online calculator is available (https://makbn.shinyapps.io/SBS_shiny/). Conclusions: SBS, a Pythagorean-based metric combining operative time and aBL, accurately predicts complications. The SBS-based model offers strong predictive utility for risk stratification.
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