Zhao Lingyun, Heng Hongyan, Xie Qinyuan, Liang Chenghong, Guo Sijia, Zhang Ziyi, Yuan Huijuan
Department of Endocrinology, Zhengzhou University People's Hospital, Zhengzhou, China.
Department of Endocrinology, Henan Provincial Key Medicine Laboratory of Intestinal Microecology and Diabetes, Diabetes Microecology Diagnosis and Treatment and Transformation Engineering Research Center of Henan Province, Henan Provincial People's Hospital, Zhengzhou, China.
Front Endocrinol (Lausanne). 2025 Jun 19;16:1563734. doi: 10.3389/fendo.2025.1563734. eCollection 2025.
To investigate the association between the Glycemic Risk Index (GRI) and carotid intima-media thickness (CIMT) in type 2 diabetes mellitus (T2DM) patients and evaluate the clinical utility of GRI for early vascular risk assessment.
This retrospective study included 450 previously untreated patients with T2DM prior to hospitalization. We calculated GRI using CGM data and assessed CIMT with high-resolution ultrasound. Multiple linear and logistic regression analyses assessed the association between GRI and CIMT. Receiver operating characteristic (ROC) curve analyses evaluated GRI's predictive performance.
There was a significant positive correlation between GRI and CIMT (r = 0.42, P < 0.001). After adjusting for confounders, GRI remained an independent predictor of CIMT thickening (OR = 7.226, 95% CI: 5.597-8.856, P < 0.001). ROC analysis revealed that GRI alone predicted abnormal CIMT with an AUC of 0.869.
GRI is a robust marker for predicting CIMT thickening in T2DM patients, providing a novel approach for cardiovascular risk stratification. This study underscores the potential of integrating GRI into routine diabetes management to improve vascular outcomes.
探讨2型糖尿病（T2DM）患者的血糖风险指数（GRI）与颈动脉内膜中层厚度（CIMT）之间的关联，并评估GRI在早期血管风险评估中的临床应用价值。
这项回顾性研究纳入了450例住院前未经治疗的T2DM患者。我们使用连续血糖监测（CGM）数据计算GRI，并采用高分辨率超声评估CIMT。多元线性和逻辑回归分析评估GRI与CIMT之间的关联。受试者工作特征（ROC）曲线分析评估GRI的预测性能。
GRI与CIMT之间存在显著正相关（r = 0.42，P < 0.001）。在调整混杂因素后，GRI仍然是CIMT增厚的独立预测因素（OR = 7.226，95%CI：5.597 - 8.856，P < 0.001）。ROC分析显示，单独使用GRI预测CIMT异常的曲线下面积（AUC）为0.869。
GRI是预测T2DM患者CIMT增厚的可靠标志物，为心血管风险分层提供了一种新方法。本研究强调了将GRI纳入常规糖尿病管理以改善血管结局的潜力。
