Centre de Recherche en Nutrition Humaine Rhône-Alpes, Univ-Lyon, CarMeN Laboratory, INSERM, INRA, INSA Lyon, Université Claude Bernard Lyon 1, Hospices Civils de Lyon, F-CRIN/FORCE Network, Pierre Bénite, France.
Nutrition Research, Mondelez International, Saclay, France.
Front Endocrinol (Lausanne). 2021 Sep 9;12:666008. doi: 10.3389/fendo.2021.666008. eCollection 2021.
Glycemic variability (GV) appears today as an integral component of glucose homeostasis for the management of type 2 diabetes (T2D). This review aims at investigating the use and relevance of GV parameters in interventional and observational studies for glucose control management in T2D. It will first focus on the relationships between GV parameters measured by continuous glucose monitoring system (CGMS) and glycemic control and T2D-associated complications markers. The second part will be dedicated to the analysis of GV parameters from CGMS as outcomes in interventional studies (pharmacological, nutritional, physical activity) aimed at improving glycemic control in patients with T2D. From 243 articles first identified, 63 articles were included (27 for the first part and 38 for the second part). For both analyses, the majority of the identified studies were pharmacological. Lifestyle studies (including nutritional and physical activity-based studies, N-AP) were poorly represented. Concerning the relationships of GV parameters with those for glycemic control and T2D related-complications, the standard deviation (SD), the coefficient of variation (CV), the mean blood glucose (MBG), and the mean amplitude of the glycemic excursions (MAGEs) were the most studied, showing strong relationships, in particular with HbA1c. Regarding the use and relevance of GV as an outcome in interventional studies, in pharmacological ones, SD, MAGE, MBG, and time in range (TIR) were the GV parameters used as main criteria in most studies, showing significant improvement after intervention, in parallel or not with glycemic control parameters' (HbA1c, FBG, and PPBG) improvement. In N-AP studies, the same results were observed for SD, MAGE, and TIR. Despite the small number of N-AP studies addressing both GV and glycemic control parameters compared to pharmacological ones, N-AP studies have shown promising results on GV parameters and would require more in-depth work. Evaluating CGMS-GV parameters as outcomes in interventional studies may provide a more integrative dimension of glucose control than the standard postprandial follow-up. GV appears to be a key component of T2D dysglycemia, and some parameters such as MAGE, SD, or TIR could be used routinely in addition to classical markers of glycemic control such as HbA1c, fasting, or postprandial glycemia.
血糖变异性（GV）如今已成为 2 型糖尿病（T2D）管理中血糖稳态的一个组成部分。本综述旨在研究 GV 参数在 T2D 血糖控制管理的干预和观察性研究中的应用和相关性。它将首先关注通过连续血糖监测系统（CGMS）测量的 GV 参数与血糖控制和 T2D 相关并发症标志物之间的关系。第二部分将专门分析 CGMS 中 GV 参数作为干预研究（药物、营养、体力活动）的结果，这些研究旨在改善 T2D 患者的血糖控制。从最初确定的 243 篇文章中，有 63 篇文章被纳入（第一部分 27 篇，第二部分 38 篇）。对于这两种分析，大多数确定的研究都是药物治疗。生活方式研究（包括营养和基于体力活动的研究，N-AP）的代表性不足。关于 GV 参数与血糖控制和 T2D 相关并发症之间的关系，标准差（SD）、变异系数（CV）、平均血糖（MBG）和血糖波动幅度（MAGEs）是研究最多的参数，它们之间存在很强的关系，特别是与 HbA1c 之间。关于 GV 作为干预研究结果的应用和相关性，在药物治疗研究中，SD、MAGE、MBG 和血糖控制达标时间（TIR）是大多数研究中作为主要标准的 GV 参数，这些参数在干预后显示出显著改善，与血糖控制参数（HbA1c、FBG 和 PPBG）的改善平行或不平行。在 N-AP 研究中，SD、MAGE 和 TIR 也得到了同样的结果。尽管与药物治疗研究相比，N-AP 研究同时涉及 GV 和血糖控制参数的数量较少，但 N-AP 研究已经显示出对 GV 参数有希望的结果，需要进一步深入研究。在干预性研究中，将 CGMS-GV 参数评估为结果可能比常规餐后随访提供更综合的血糖控制维度。GV 似乎是 T2D 糖代谢紊乱的一个关键组成部分，一些参数，如 MAGE、SD 或 TIR，可以与 HbA1c、空腹或餐后血糖等经典血糖控制标志物一起常规使用。
