Institute of Clinical Research, University of Montpellier, Montpellier, France
Department of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital, Lausanne, Switzerland.
Diabetes Care. 2020 Apr;43(4):821-827. doi: 10.2337/dc19-1549. Epub 2020 Jan 27.
To evaluate the respective contributions of short-term glycemic variability and mean daily glucose (MDG) concentration to the risk of hypoglycemia in type 1 diabetes.
People with type 1 diabetes ( = 100) investigated at the University Hospital of Montpellier (France) underwent continuous glucose monitoring (CGM) on two consecutive days, providing a total of 200 24-h glycemic profiles. The following parameters were computed: MDG concentration, within-day glycemic variability (coefficient of variation for glucose [%CV]), and risk of hypoglycemia (presented as the percentage of time spent below three glycemic thresholds: 3.9, 3.45, and 3.0 mmol/L).
MDG was significantly higher, and %CV significantly lower (both < 0.001), when comparing the 24-h glycemic profiles according to whether no time or a certain duration of time was spent below the thresholds. Univariate regression analyses showed that MDG and %CV were the two explanatory variables that entered the model with the outcome variable (time spent below the thresholds). The classification and regression tree procedure indicated that the predominant predictor for hypoglycemia was %CV when the threshold was 3.0 mmol/L. In people with mean glucose ≤7.8 mmol/L, the time spent below 3.0 mmol/L was shortest ( < 0.001) when %CV was below 34%.
In type 1 diabetes, short-term glycemic variability relative to mean glucose (i.e., %CV) explains more hypoglycemia than does mean glucose alone when the glucose threshold is 3.0 mmol/L. Minimizing the risk of hypoglycemia requires a %CV below 34%.
评估短期血糖变异性和平均每日血糖（MDG）浓度对 1 型糖尿病患者发生低血糖的风险各自的贡献。
在蒙彼利埃大学医院（法国）接受检查的 1 型糖尿病患者（n=100）连续两天接受连续血糖监测（CGM），共提供 200 个 24 小时血糖谱。计算了以下参数：MDG 浓度、日内血糖变异性（葡萄糖变异系数[%CV]）和低血糖风险（表示为低于三个血糖阈值的时间百分比：3.9、3.45 和 3.0 mmol/L）。
根据是否有时间或一定时间低于阈值，比较 24 小时血糖谱时，MDG 显著升高，%CV 显著降低（均<0.001）。单变量回归分析表明，MDG 和%CV 是与结局变量（低于阈值的时间）一起进入模型的两个解释变量。分类和回归树程序表明，当阈值为 3.0 mmol/L 时，预测低血糖的主要指标是%CV。在平均血糖≤7.8 mmol/L 的人群中，当%CV 低于 34%时，低于 3.0 mmol/L 的时间最短（<0.001）。
在 1 型糖尿病中，当血糖阈值为 3.0 mmol/L 时，与平均血糖（即%CV）相比，短期血糖变异性相对于平均血糖（即%CV）更能解释低血糖的发生，将低血糖风险降至 34%以下。
