Do Metrics of Temporal Glycemic Variability Reveal Abnormal Glucose Rates of Change in Type 1 Diabetes?

IF 4.1 Q2 ENDOCRINOLOGY & METABOLISM
Robert Richardson
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Abstract

Background: We aimed to identify the normal range of glucose rates of change (RoC) observed in health and assess whether existing metrics of temporal glycemic variability (GV-timing), such as mean absolute glucose change (MAG) and continuous overlapping net glycemic action (CONGA), are predictive of abnormally rapid RoC in type 1 diabetes (T1D).

Methods: We identified the normal range of RoC over one-hour intervals from continuous glucose monitoring (CGM) data of healthy individuals. Rapidly rising glucose was defined as RoC values above percentiles 99% (level 1, L1) or 99.9% (level 2, L2), and rapidly falling glucose as below 1% (L1) or 0.1% (L2). The percentage of time these thresholds are exceeded in a given individual is referred to as time in fluctuation (TIF). In a separate CGM dataset of 736 T1D individuals, we calculated TIF-L1 and TIF-L2, and compared them against corresponding values of MAG and CONGA.

Results: The extremum percentiles of RoC observed in health are 0.1%: -80 mg/dL/h, 1%: -50 mg/dL, 99%: +56 mg/dL/h, and 99.9%: +89 mg/dL/h. The T1D individuals spend significantly more TIF at rates exceeding these thresholds (TIF-L1: median, 16.7% [interquartile range, 12.7-21.5], TIF-L2: 5.0% [3.1-7.8]) than healthy individuals (TIF-L1: 1.4% [0.6-2.8], TIF-L2: 0.0% [0.0-0.2]). Both MAG and CONGA are highly correlated with TIF-L1 and TIF-L2 (r > .95 in each pairwise comparison).

Conclusions: Individuals with T1D spend significant time with glucose RoC exceeding those observed in health. Existing GV-timing metrics are strongly correlated with time with abnormal RoC. Incorporation of a GV-timing metric in clinical practice is recommended.

时间血糖变异性指标是否能揭示 1 型糖尿病患者的异常血糖变化率?
背景:我们旨在确定健康人血糖变化率(RoC)的正常范围,并评估现有的时间血糖变异性(GV-timing)指标,如平均绝对血糖变化率(MAG)和连续重叠净血糖作用(CONGA),是否能预测 1 型糖尿病(T1D)中异常快速的 RoC:我们从健康人的连续血糖监测(CGM)数据中确定了一小时间隔内 RoC 的正常范围。血糖快速升高被定义为 RoC 值高于百分位数 99%(1 级,L1)或 99.9%(2 级,L2),血糖快速下降被定义为低于 1%(L1)或 0.1%(L2)。特定个体超过这些阈值的时间百分比称为波动时间(TIF)。在由 736 名 T1D 患者组成的单独 CGM 数据集中,我们计算了 TIF-L1 和 TIF-L2,并将其与 MAG 和 CONGA 的相应值进行了比较:结果:在健康状况下观察到的 RoC 极值百分位数为 0.1%:结果:在健康状态下观察到的 RoC 极值百分位数为 0.1%:-80 毫克/分升/小时,1%:-50 毫克/分升,99%:+56 毫克/分升/小时,+50 毫克/分升/小时:+56毫克/分升/小时,以及99.9%:+89毫克/分升/小时。与健康人(TIF-L1:1.4% [0.6-2.8];TIF-L2:0.0% [0.0-0.2])相比,T1D 患者花费的 TIF 超过这些阈值的比例明显更高(TIF-L1:中位数,16.7% [四分位数间距,12.7-21.5];TIF-L2:5.0% [3.1-7.8])。MAG和CONGA均与TIF-L1和TIF-L2高度相关(每对比较中的r>.95):结论:T1D 患者在血糖 RoC 上花费的时间远远超过健康状态下的血糖 RoC。现有的 GV 定时指标与异常 RoC 时间密切相关。建议在临床实践中采用 GV 定时指标。
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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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