4.4 Review

Glucose Variability: A Review of Clinical Applications and Research Developments

期刊

DIABETES TECHNOLOGY & THERAPEUTICS
卷 20, 期 -, 页码 5-15

出版社

MARY ANN LIEBERT, INC
DOI: 10.1089/dia.2018.0092

关键词

Glycemic variability; Hypoglycemia; Hyperglycemia; Ambulatory glucose profile; Continuous glucose monitoring; Time series analysis

向作者/读者索取更多资源

Glycemic variability (GV) is a major consideration when evaluating quality of glycemic control. GV increases progressively from prediabetes through advanced T2D and is still higher in T1D. GV is correlated with risk of hypoglycemia. The most popular metrics for GV are the %Coefficient of Variation (%CV) and standard deviation (SD). The %CV is correlated with risk of hypoglycemia. Graphical display of glucose by date, time of day, and day of the week, and display of simplified glucose distributions showing % of time in several ranges, provide clinically useful indicators of GV. SD is highly correlated with most other measures of GV, including interquartile range, mean amplitude of glycemic excursion, mean of daily differences, and average daily risk range. Some metrics are sensitive to the frequency, periodicity, and complexity of glycemic fluctuations, including Fourier analysis, periodograms, frequency spectrum, multiscale entropy (MSE), and Glucose Variability Percentage (GVP). Fourier analysis indicates progressive changes from normal subjects to children and adults with T1D, and from prediabetes to T2D. The GVP identifies novel characteristics for children, adolescents, and adults with type 1 diabetes and for adults with type 2. GVP also demonstrated small rapid glycemic fluctuations in people with T1D when using a dual-hormone closed-loop control. MSE demonstrated systematic changes from normal subjects to people with T2D at various stages of duration, intensity of therapy, and quality of glycemic control. We describe new metrics to characterize postprandial excursions, day-to-day stability of glucose patterns, and systematic changes of patterns by day of the week. Metrics for GV should be interpreted in terms of percentiles and z-scores relative to identified reference populations. There is a need for large accessible databases for reference populations to provide a basis for automated interpretation of GV and other features of continuous glucose monitoring records.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据