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- Title
Modified triglyceride-glucose index indices are reliable markers for predicting risk of metabolic dysfunction-associated fatty liver disease: a cross-sectional study.
- Authors
Ae Hee Kim; Da-Hye Son; Yong-Jae Lee
- Abstract
Introduction: Metabolic dysfunction-associated fatty liver disease (MAFLD) is newly proposed nomenclature, and its diagnosis involves an algorithm that can be complicated and impractical for clinicians in real-world clinical settings. Thus, we investigated the association between MAFLD and modified triglycerideglucose index (TyG) indices to find a more concise, feasible method for predicting MAFLD in everyday clinical care. Methods: Data were obtained from people who voluntarily underwent health check-ups at the Health Promotion Centre of Gangnam Severance Hospital, Yonsei University College of Medicine, from January 2017 to October 2020. Four indices were analyzed: TyG-body to mass index (BMI), TyG-waist circumference (WC), TyG, and the fatty liver index (FLI). The odds ratios for MAFLD according to each index were calculated using multiple logistic regression analyses, and the receiver operating characteristics curve (ROC) and area under the ROC were obtained to find the predictive powers of each index. Results: The final number of study participants was 22,391, 8,246 with MAFLD and 14,145 without MAFLD. The odds ratios (95% confidence intervals) from TyGWC and TyG-BMI after adjusting for confounding variables were 12.484 (9.962-15.644) and 12.494 (9.790-15.946), respectively, for quartile 2, 54.332 (43.131-68.442) and 51.580 (40.495-65.699) for quartile 3, and 165.804 (130.243-211.076) and 128.592 (100.601-164.371) for quartile 4. The area under the ROC curve values for TyG-WC and TyG-BMI were 0.862 (0.857-0.867) and 0.867 (0.862-0.872), respectively. Conclusion: The modified TyG indices are highly reliable markers for predicting MAFLD that clinicians can easily and practically apply in everyday, real-world, clinical care settings.
- Subjects
YONSEI University; FATTY liver; TRIGLYCERIDES; RECEIVER operating characteristic curves; MULTIPLE regression analysis; LOGISTIC regression analysis; CROSS-sectional method
- Publication
Frontiers in Endocrinology, 2024, p1
- ISSN
1664-2392
- Publication type
Article
- DOI
10.3389/fendo.2023.1308265