Adiposity and Metabolic Indices in the Diagnosis and Histological Stage Association of Metabolic Dysfunction-Associated Steatotic Liver Disease

脂肪组织和代谢指标在代谢功能障碍相关脂肪肝疾病的诊断和组织学分期中的作用

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Abstract

Background: Metabolic dysfunction-associated steatotic liver disease (MALSD) is defined as the excessive accumulation of triglycerides in the liver in the presence of at least one cardiometabolic risk factor and liver biopsy remains the diagnostic gold standard. This study aimed to evaluate the diagnostic performance of adiposity and metabolism related indices for the non-invasive detection of MASLD and the metabolic dysfunction-associated steatohepatitis (MASH). Methods: A cross-sectional study was conducted in 161 Mexican adults undergoing laparoscopic cholecystectomy, during which liver biopsies were obtained for histological evaluation. Indices such as the Hepatic Steatosis Index (HSI), the Triglyceride-Glucose index (TyG), TyG-BMI (TyG adjusted for body mass index), and TyG-WC (TyG adjusted for waist circumference), among others, were calculated. Results: Of the 161 participants, 66 were diagnosed with MASLD, and 50 of them had histological evidence of MASH. All adiposity and metabolic indices evaluated were significantly higher in MASLD patients compared with controls. Logistic regression identified HSI, TyG, TyG-BMI, and TyG-WC as independently associated with MASLD and MASH, with TyG showing the strongest association. Correlation analyses demonstrated that TyG-BMI and TyG-WC were most strongly associated with histological features of MASH. Receiver operating characteristic curve analyses showed that TyG-WC had the highest diagnostic accuracy for MASLD (AUC 0.721, 95% CI 0.641-0.802) and MASH (AUC 0.735, 95% CI 0.648-0.823), while TyG-BMI displayed high sensitivity (0.758 for MASLD; 0.780 for MASH). Conclusions: Triglyceride-glucose-based indices, particularly TyG-WC and TyG-BMI, showed the highest diagnostic performance for detecting MASLD and MASH, suggesting that these indices may serve as practical, non-invasive tools for identifying individuals at risk.

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