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Published on: July 19, 2024
Estimated Glucose Disposal Rate Predicts the Risk of Incident Metabolic Dysfunction-Associated Steatotic Liver
Takahiro Ichikawa1, Yoshitaka Hashimoto2, Takuro Okamura1
1Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan.
Objectives:
There is a relationship between insulin resistance and metabolic dysfunction-associated steatotic liver disease (MASLD) and the estimated glucose disposal rate (eGDR), which has been reported as a surrogate marker of insulin resistance. This study aimed to investigate the association between eGDR and the incident MASLD, and compare the ability to predict incident MASLD with other insulin resistance markers.
Methods:
Retrospective cohort data from a health check-up program were analyzed. Participants were categorized into 4 subgroups according to eGDR quartiles. To assess the association between eGDR quartiles and incident MASLD, logistic regression analyses were used. Additionally, to compare the predictive ability of eGDR, triglyceride/high-density lipoprotein (HDL) cholesterol (TG/HDL) ratio, and triglyceride glucose index with respect to incident MASLD, receiver operating characteristics analysis was used.
Results:
Of 16 689 participants were included, 3654 developed MASLD. After multivariate adjustment, compared with the lowest eGDR quartile, odds ratios (95% confidence interval [CI]) for incident MASLD in the second, third, and highest GDR quartiles, were 0.775 (0.692-0.868), 0.478 (0.408-0.560), and 0.147 (0.110-0194), respectively. The association between lower eGDR levels and MASLD risk remained consistent across stratification by sex and obesity status. Moreover, the area under the receiver operating characteristics curve (95% CI) for eGDR (0.8 [0.79-0.81]) was higher than for TG/HDL ratio 0.76 [0.79-0.81]) and triglyceride glucose index (0.75 [0.74-0.76]).
Conclusions:
Lower eGDR levels were associated with an increased risk of incident MASLD. Our findings suggest that eGDR may be a more effective tool for predicting MASLD risk.
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