Department of Metabolism & Endocrinology, Juntendo University Graduate School of Medicine, Hongo 2-1-1 Bunkyo-ku, Tokyo, Japan.
Department of Metabolic Medicine, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, Japan.
Cardiovasc Diabetol. 2021 Jan 7;20(1):15. doi: 10.1186/s12933-020-01194-2.
Previous studies have suggested that high mean glucose levels and glycemic abnormalities such as glucose fluctuation and hypoglycemia accelerate the progression of atherosclerosis in patients with type 2 diabetes. Although continuous glucose monitoring (CGM) that could evaluate such glycemic abnormalities has been rapidly adopted, the associations between CGM-derived metrics and arterial stiffness are not entirely clear.
This exploratory cross-sectional study used baseline data from an ongoing prospective, multicenter, observational study with 5 years of follow-up. Study participants included 445 outpatients with type 2 diabetes and no history of apparent cardiovascular disease who underwent CGM and brachial-ankle pulse wave velocity (baPWV) measurement at baseline. Associations between CGM-derived metrics and baPWV were analyzed using multivariate regression models.
In a linear regression model, all CGM-derived metrics were significantly associated with baPWV, but HbA1c was not. Some CGM-derived metrics related to intra-day glucose variability, hyperglycemia, and hypoglycemia remained significantly associated with baPWV after adjusting for possible atherosclerotic risk factors, including HbA1c. Based on baPWV ≥ 1800 cm/s as indicative of high arterial stiffness, multivariate logistic regression found that some CGM-derived metrics related to intra-day glucose variability and hyperglycemia are significantly associated with high arterial stiffness even after adjusting for possible atherosclerotic risk factors, including HbA1c.
Multiple CGM-derived metrics are significantly associated with baPWV and high arterial stiffness in patients with type 2 diabetes who have no history of apparent cardiovascular disease. These metrics might be useful for identifying patients at high risk of developing cardiovascular disease.
先前的研究表明,高平均血糖水平和血糖异常,如血糖波动和低血糖,会加速 2 型糖尿病患者动脉粥样硬化的进展。尽管能够评估此类血糖异常的连续血糖监测(CGM)已被迅速采用,但 CGM 衍生指标与动脉僵硬之间的关系尚不完全清楚。
本探索性横断面研究使用了一项正在进行的前瞻性、多中心、观察性研究的基线数据,该研究有 5 年的随访期。研究参与者包括 445 名 2 型糖尿病且无明显心血管疾病病史的门诊患者,他们在基线时接受了 CGM 和肱踝脉搏波速度(baPWV)测量。使用多变量回归模型分析 CGM 衍生指标与 baPWV 之间的关系。
在线性回归模型中,所有 CGM 衍生指标均与 baPWV 显著相关,但 HbA1c 则不然。在调整可能的动脉粥样硬化危险因素(包括 HbA1c)后,一些与日间血糖变异性、高血糖和低血糖相关的 CGM 衍生指标仍与 baPWV 显著相关。基于 baPWV≥1800cm/s 作为动脉僵硬程度较高的指标,多变量逻辑回归发现,一些与日间血糖变异性和高血糖相关的 CGM 衍生指标与高动脉僵硬程度显著相关,即使在调整可能的动脉粥样硬化危险因素(包括 HbA1c)后也是如此。
在无明显心血管疾病病史的 2 型糖尿病患者中,多种 CGM 衍生指标与 baPWV 和高动脉僵硬程度显著相关。这些指标可能有助于识别发生心血管疾病风险较高的患者。