Diagnostic Utility of Lipid Indices for Detecting MASLD in Patients with Metabolic Syndrome
Eunice Susan Thomson, Akash Thomas Oommen
Asian Journal of Medicine and Health · pp. 174–184 · Published 29 Jul 2025
10.9734/ajmah/2025/v23i71277Abstract
Background: Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is a prevalent hepatic manifestation of metabolic syndrome and is emerging as a leading cause of chronic liver disease globally. Early detection is essential for effective risk stratification and intervention. Lipid abnormalities – especially elevated triglycerides - are central to MASLD pathophysiology and may serve as cost-effective, non-invasive diagnostic indicators. Objectives: To evaluate the clinical utility of lipid parameters and lipid-derived indices in predicting the presence and severity of MASLD in adults with metabolic syndrome. Methodology: A prospective observational study was conducted at a tertiary care hospital in 2024. A total of 110 adult patients with metabolic syndrome were enrolled. Anthropometric data, fasting lipid profiles, liver enzymes, glucose metabolism markers and derived indices (TG/HDL, TG/LDL, TG/Total Cholesterol, HDL/LDL and TyG index) were assessed. Abdominal ultrasonography was used to classify MASLD severity. Statistical analyses included ROC curves, Pearson correlation, t-tests and chi-square tests were done. Results: Triglyceride levels were significantly higher in patients with MASLD (median 112.00 vs. 92.00 mg/dL, p = 0.0001), whereas HDL, LDL and total cholesterol showed no significant differences. ROC analysis indicated that the TG/Total Cholesterol ratio had the highest discriminative power (AUC = 0.70, p < 0.001), followed by TG/HDL (AUC = 0.64, p = 0.010), TyG index (AUC = 0.64, p = 0.007) and TG/LDL (AUC = 0.63, p = 0.016). The HDL/LDL ratio was not predictive (AUC = 0.46, p = 0.484). Conclusion: Triglyceride-based indices- especially TG/Total Cholesterol and TG/HDL, demonstrate strong potential as non-invasive predictors of MASLD. These markers may complement imaging tools and support early screening in metabolic syndrome patients, enhancing timely intervention and clinical outcomes.
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