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Correlation between alternative insulin resistance indexes and diabetic kidney disease: a retrospective study
Xiaodie Mu1, Aihua Wu1, Huiyue Hu1
1Department of Nephrology, Third Affiliated Hospital of Soochow University, Changzhou, 213003, China.
Purpose:
This retrospective study aimed to investigate the relationship between alternative insulin resistance (IR) indexes not reliant on insulin and diabetic kidney disease (DKD) incidence in a newly diagnosed cohort of individuals with type 2 diabetes mellitus (T2DM).
Methods:
We conducted a retrospective analysis of baseline characteristics in a cohort of 521 individuals with T2DM, then followed up on the outcome of DKD. To assess the predictive ability of IR indexes, we compared the performance of four non-insulin-based IR indexes and the homeostasis model for insulin resistance (HOMA-IR) using logistic regression and consistency-statistics (C-statistics). Furthermore, we computed the net reclassification index (NRI) and integrated discrimination improvement (IDI) to evaluate the additional effects of the indexes.
Results:
The four alternative IR indexes of DKD patients were significantly higher than those of non-DKD. After adjustment for other variables, the highest tertile of all indexes was significantly related to DKD incidence, compared with the lowest tertile. Furthermore, the C-statistics for the triglyceride-glucose index (TyG index) and triglyceride to high-density lipoprotein ratio (TG/HDL) were all 0.652, while triglyceride glucose-body mass index (TyG-BMI) and metabolic score for insulin resistance (METS-IR) were 0.639 and 0.651, respectively. The incorporation of the alternative IR indexes into the baseline model revealed positive additional effects, leading to an improved prediction of the risk for DKD.
Conclusions:
It was discovered that the alternative IR indexes served as independent risk factors of DKD. Among the four alternative indexes, TyG index and TG/HDL had the best prediction performance for DKD, followed by METS-IR.
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