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Updated: Jan 17, 2026

Optimized Analysis of In Vivo and In Vitro Hepatic Steatosis
Published on: March 11, 2017
Triglyceride Glucose Index and Related Parameters Are Effective Biomarkers to Identify Metabolic
Magdy H Megalaa1, Ahmed Zeid2, Mohamed Zietoun1
1Diabetes, Metabolism, and Lipidology Unit, Department of Internal Medicine, Faculty of Medicine, Alexandria University, Alexandria, Egypt.
Abstract:
Background: The triglyceride-glucose (TyG) index and related parameters have recently been advocated as efficient diagnostic markers for metabolic dysfunction-associated steatotic liver disease (MASLD) in the general population. Yet, there is a paucity of data addressing their significance in MASLD diagnosis and severity assessment in the vulnerable population of type 2 diabetes mellitus (T2DM). The aim of this study was to evaluate the predictive capacity of TyG-related indices for MASLD diagnosis in patients with T2DM, and to investigate the relationship of these parameters with hepatic steatosis severity. Methods: This cross-sectional study encompassed a cohort of 600 adults diagnosed with T2DM, who were enrolled from the diabetes and metabolism outpatient clinic at Alexandria Main University Hospital. After excluding secondary causes, hepatic steatosis was diagnosed using the FibroScan 430 mini+ machine (EchoSense, Paris, France), with results expressed as the controlled attenuation parameter. Anthropometric and biochemical measurements were utilized to derive TyG-related indices, including TyG index, TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), and TyG-waist to height ratio (TyG-WHtR). Results: MASLD was diagnosed in 83% of the recruited subjects. The studied TyG-related parameters were markedly higher in patients with severe steatosis. Moreover, multivariate analysis identified TyG-BMI as an independent risk factor for severe steatosis. Furthermore, the receiver operating characteristic curve was used to assess the diagnostic performance of the studied TyG indices for detecting MASLD in individuals with T2DM. The area under the curve for each of the four indicators was as follows: 0.775 for TyG-BMI, followed by 0.755 for TyG-WC, 0.741 for TyG-WHtR, and 0.637 for TyG index. These findings revealed good predictive capacity for all four parameters, especially TyG-BMI, which exhibited the highest level of predictive accuracy. Conclusion: The TyG index and related parameters, particularly TyG-BMI, are reliable and cost-effective biomarkers for detecting and assessing the severity of MASLD.
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