Objective Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality, with post‐hepatectomy liver failure (PHLF) representing a major complication. We aimed to develop an objective, multidimensional liver function grading system via latent class analysis (LCA) and assess its predictive value for PHLF in combination with surgical parameters. Methods Among 185 HCC patients who underwent resection, the LCA incorporated nine liver function indicators, including severity of liver cirrhosis, splenomegaly, platelet count (PLT), etc., to categorize liver function into three grades: poor, intermediate, and good. Discrimination was evaluated using entropy. Restricted cubic spline analysis assessed the association between blood loss and PHLF, and multivariate logistic regression identified independent predictors. Results LCA yielded three distinct classes (entropy = 0.953). Blood loss showed a nonlinear relationship with PHLF ( p = 0.012), with a risk threshold at 150 mL. PHLF incidence was 36.6% in poor versus 11.5% in good liver function. Liver function grade and resection extent independently predicted PHLF, with consistent effects across resection subgroups (interaction p > 0.05). Conclusion This LCA‐based grading system, integrating imaging and biochemical markers, enables precise PHLF risk stratification and, combined with surgical variables, may inform individualized perioperative management in HCC resection.
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Liu et al. (2025) studied this question.
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