连续血糖监测得出的血糖风险指数与 1 型糖尿病患者心血管自主神经病变的关系:一项横断面研究

IF 4.1 Q2 ENDOCRINOLOGY & METABOLISM
Ji Eun Jun, You-Bin Lee, Jae Hyeon Kim
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引用次数: 0

摘要

背景:血糖风险指数(GRI)是一种新的连续血糖监测(CGM)综合指标,用于加权低血糖和高血糖。我们评估了 GRI 与心血管自主神经病变(CAN)之间的关联,并比较了 GRI 和传统 CGM 指标对 CAN 的影响:在这项横断面研究中,我们对 165 名 1 型糖尿病患者在进行自主神经功能测试前三个月的 CGM 数据进行了回顾性分析。CAN的定义是:根据特定年龄的参考值,副交感神经测试结果至少有两次异常:结果:CAN的总发病率为17.1%。与没有副交感神经异常的患者相比,副交感神经异常患者的 GRI 评分、目标值高于范围 (TAR)、变异系数 (CV) 和标准差 (SD) 明显更高,但在范围内的时间 (TIR) 明显更短。GRI 每增加 1 个标准差,CAN 的患病率就会在 GRI 较高的区域增加(趋势 P = .002)。在多变量模型中,TIR 和 CV 也与 CAN 显著相关。GRI预测CAN的曲线下面积(0.85,95% CI:0.76-0.94)优于TIR(0.80,95% CI:0.71-0.89,比较P = .046)或CV(0.71,95% CI:0.57-0.84,比较P = .049):结论:GRI 与 1 型糖尿病患者的 CAN 密切相关,可能是比 TIR 更好的预测 CAN 的 CGM 指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association of Continuous Glucose Monitoring-Derived Glycemia Risk Index With Cardiovascular Autonomic Neuropathy in Patients With Type 1 Diabetes Mellitus: A Cross-sectional Study.

Background: The glycemia risk index (GRI) is a new composite continuous glucose monitoring (CGM) metric for weighted hypoglycemia and hyperglycemia. We evaluated the association between the GRI and cardiovascular autonomic neuropathy (CAN) and compared the effects of the GRI and conventional CGM metrics on CAN.

Methods: For this cross-sectional study, three-month CGM data were retrospectively analyzed before autonomic function tests were performed in 165 patients with type 1 diabetes. CAN was defined as at least two abnormal results of parasympathetic tests according to an age-specific reference.

Results: The overall prevalence of CAN was 17.1%. Patients with CAN had significantly higher GRI scores, target above range (TAR), coefficient of variation (CV), and standard deviation (SD) but significantly lower time in range (TIR) than those without CAN. The prevalence of CAN increased across higher GRI zones (P for trend <.001). A multivariate logistic regression analysis, adjusted for covariates such as HbA1c, demonstrated that the odds ratio (OR) of CAN was 9.05 (95% confidence interval [CI]: 2.21-36.96, P = .002) per 1-SD increase in the GRI. TIR and CV were also significantly associated with CAN in the multivariate model. The area under the curve of GRI for the prediction of CAN (0.85, 95% CI: 0.76-0.94) was superior to that of TIR (0.80, 95% CI: 0.71-0.89, P for comparison = .046) or CV (0.71, 95% CI: 0.57-0.84, P for comparison = .049).

Conclusions: The GRI is significantly associated with CAN in patients with type 1 diabetes and may be a better CGM metric than TIR for predicting CAN.

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来源期刊
Journal of Diabetes Science and Technology
Journal of Diabetes Science and Technology Medicine-Internal Medicine
CiteScore
7.50
自引率
12.00%
发文量
148
期刊介绍: The Journal of Diabetes Science and Technology (JDST) is a bi-monthly, peer-reviewed scientific journal published by the Diabetes Technology Society. JDST covers scientific and clinical aspects of diabetes technology including glucose monitoring, insulin and metabolic peptide delivery, the artificial pancreas, digital health, precision medicine, social media, cybersecurity, software for modeling, physiologic monitoring, technology for managing obesity, and diagnostic tests of glycation. The journal also covers the development and use of mobile applications and wireless communication, as well as bioengineered tools such as MEMS, new biomaterials, and nanotechnology to develop new sensors. Articles in JDST cover both basic research and clinical applications of technologies being developed to help people with diabetes.
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