不同胰岛素抵抗相关指标作为生物标志物预测2型糖尿病患者外周动脉病变的价值及比较研究

Value and Comparison of Insulin Resistance-Related Indexes as Biomarkers in Predicting Peripheral Artery Disease in Type 2 Diabetes Mellitus

摘要: 目的：本研究旨在探讨8种胰岛素抵抗(IR)相关指标[三酰甘油与葡萄糖乘积指数(TyG)、三酰甘油葡萄糖体质量指数(TyG-BMI)、三酰甘油–高密度脂蛋白胆固醇指数(TG/HDL-C)、胰岛素抵抗代谢指数(METS-IR)、稳态模型评估胰岛素抵抗指数(HOMA-IR)、非高密度脂蛋白胆固醇–高密度脂蛋白胆固醇指(Non-HDL-C/HDL-C)、脂质心血管指数(LCI)、胆固醇指数(CI)]作为生物标志物预测2型糖尿病(T2DM)患者外周动脉病变(PAD)的价值，并比较其预测效能。方法：回顾性收集2023年1月至2024年12月于宁夏回族自治区人民医院内分泌科住院期间收住的1055例T2DM患者临床资料，根据多普勒超声结果分为PAD组(420例)和非PAD组(635例)。采用统计学方法比较两组一般资料及生化指标的差异，通过Logistic回归分析IR相关指标与PAD的关联，运用ROC曲线、重分类改善指标(NRI)及综合判别改善指标(IDI)评估各指标的预测效能。结果：结果显示，PAD组的8种IR相关指标水平均显著高于非PAD组(P < 0.05)，且与PAD风险呈正相关及剂量–反应关系(P < 0.05)。ROC曲线分析结果显示，TG/HDL-C指数的预测效能最佳(AUC = 0.689)，而TyG指数的灵敏度最高(87.4%)。NRI和IDI分析表明，TyG指数在提升模型预测效能上表现最优。结论：TG/HDL-C指数和TyG指数可作为预测T2DM患者发生PAD的优质生物标志物，其中TG/HDL-C指数因检测便捷、效能突出，更适合在基层医疗机构推广应用。

Abstract: Objective: The purpose of this study is to explore the value of eight insulin resistance (IR)-related indicators [triglyceride-glucose index (TyG), triglyceride-glucose-body mass index (TyG-BMI), triglyceride-high-density lipoprotein cholesterol index (TG/HDL-C), metabolic score for insulin resistance (METS-IR), homeostasis model assessment of insulin resistance (HOMA-IR), non-high-density lipoprotein cholesterol-high-density lipoprotein cholesterol index (Non-HDL-C/HDL-C), lipid cardiovascular index (LCI), and cholesterol index (CI)] as biomarkers in predicting peripheral artery disease (PAD) in patients with type 2 diabetes mellitus (T2DM), and to compare their predictive efficacy. Methods: The clinical data of 1055 T2DM patients who were hospitalized in the Endocrinology Department of Ningxia Uygur Autonomous Region People’s Hospital from January 2023 to December 2024 were retrospectively collected. According to the results of vascular color Doppler ultrasound, the patients were divided into the PAD group (420 cases) and the non-PAD group (635 cases). Statistical methods were used to analyze the differences in general data and biochemical indicators between the two groups. Logistic regression was employed to explore the association between IR-related indicators and PAD. ROC curves, NRI and IDI were used to evaluate the predictive efficacy of each indicator. Results: The results showed that the levels of the 8 IR-related indicators in the PAD group were significantly higher than those in the non-PAD group (P < 0.05), and were positively correlated with and showed a dose-response relationship with the risk of PAD (P < 0.05). In the ROC curve analysis, the TG/HDL-C index had the best predictive efficacy (AUC = 0.689), and the TyG index had the highest sensitivity (87.4%). The NRI and IDI analyses indicated that the TyG index performed the best in improving the predictive efficacy of the model. Conclusion: TG/HDL-C index and TyG index can be used as high quality biomarkers for predicting PAD in patients with T2DM. TG/HDL-C index is more suitable for popularization and application in primary medical institutions because of its convenient detection and outstanding efficacy.