# The predictive value of surrogate insulin resistance indices for T2DM complicated with metabolic syndrome: a retrospective study based on hospitalized patients in China

## TL;DR

This study evaluates how well certain blood markers predict type 2 diabetes complicated by metabolic syndrome in hospitalized Chinese patients.

## Contribution

The study identifies the TG/HDL-C ratio as the best predictor of T2DM with MetS and develops a predictive nomogram model.

## Key findings

- The TG/HDL-C ratio had the highest predictive accuracy (AUC=0.915) for T2DM with MetS.
- A nomogram model using TG/HDL-C ratio, sex, WHR, and FCP achieved strong predictive performance (C-index=0.922).
- The model showed good calibration and clinical utility for early identification of T2DM with MetS.

## Abstract

To evaluate the predictive value of surrogate indices of insulin resistance (IR)- specifically, the triglyceride-glucose (TyG) index, the triglyceride glucose-body mass (TyG-BMI) index, and the triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) for metabolic syndrome (MetS) in patients with type 2 diabetes mellitus (T2DM).

A single-center, retrospective study was conducted involving 2409 T2DM patients. Based on the presence of MetS, participants were divided into a T2DM-MetS group (n=1,787) and a T2DM-only group (n=622). Logistic regression was used to analyze the influencing factors for T2DM complicated with MetS, and to compare the predictive value of the TyG index, the TyG-BMI index, and the TG/HDL-C ratio. A nomogram prediction model was constructed. The model’s discriminative ability, clinical utility, and calibration were evaluated using the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and a calibration curve, respectively.

The multivariate logistic regression analysis model revealed that Sex, Wasit-to-hip ratio (WHR), fasting C-Peptide (FCP), 2-hour C-Peptide (2hCP), the TyG index, the TyG-BMI index, and the TG/HDL-C ratio were risk factors for T2DM complicated with MetS. The area under the curve (AUC) for the TyG index, the TyG-BMI index, and the TG/HDL-C ratio in predicting T2DM complicated with MetS were 0.809, 0.807, and 0.915, respectively. The prediction model was constructed using the TG/HDL-C ratio, Sex, WHR, and FCP. The model demonstrated that the C-index for predicting the presence of MetS in T2DM patients was 0.922 (95% CI: 0.909, 0.936). The DCA showed a maximum net benefit rate of 0.742.

The surrogate indices for IR (the TyG index, the TyG-BMI index, and the TG/HDL-C ratio) were risk factors for T2DM complicated with MetS, among which the TG/HDL-C ratio was the optimal predictor. The nomogram model constructed based on the TG/HDL-C ratio, Sex, WHR, and FCP demonstrated good predictive performance for T2DM complicated with MetS. This model shows good calibration and practicality, providing a valuable reference to aid in early identification and preventive strategies in clinical practice.