Τriglycerides-glucose (TyG) index is a sensitive marker of insulin resistance in Greek children and adolescents.

Autor: Dikaiakou, Eirini, Vlachopapadopoulou, Elpis Athina, Paschou, Stavroula A., Athanasouli, Fani, Panagiotopoulos, Ιoannis, Kafetzi, Maria, Fotinou, Aspasia, Michalacos, Stephanos
Zdroj: Endocrine (1355008X); Oct2020, Vol. 70 Issue 1, p58-64, 7p
Abstrakt: Purpose: To investigate the association between Triglyceride-glucose (TyG) index and the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) and Matsuda indices in Greek obese children and adolescents, in order to assess whether it could be used as a predictor of insulin resistance. Methods: 367 children (47.7% boys) with mean age of 9.9 ± 2.3 years, who were investigated for obesity, were included. After overnight fasting, TyG and HOMA-IR indices were calculated in all participants. In a subpopulation of 72 children Matsuda index was also calculated. Results: 48.8% and 36.1% of the participants had insulin resistance according to HOMA-IR and Matsuda index respectively. TyG was significantly and positively correlated with BMI, ΗΟΜΑ-IR, lipid profile and Matsuda index. ROC curve analysis for TyG showed that the optimal cutoff value for the prediction of insulin resistance (HOMA-IR) was 7.96 with sensitivity 65% and specificity 58%. The area under the curve (AUC) was 0.65 which significantly differs from 0.5 (p < 0.001). Similarly, the optimal cutoff value of TyG index for predicting insulin resistance as evidenced by Matsuda was 7.91 with sensitivity 85% and specificity 61%. The AUC was 0.75 (p < 0.001). The odds for insulin resistance (with HOMA-IR) was 2.54 times greater for subjects with TyG higher than 7.96, while the odds for insulin resistance (with Matsuda) was 8.56 times greater for subjects with TyG more than 7.91. Conclusions: TyG index shows a positive correlation with insulin resistance among children and adolescents, however further studies are needed to clarify its predictive ability. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index