期刊
DIABETES TECHNOLOGY & THERAPEUTICS
卷 23, 期 4, 页码 314-319出版社
MARY ANN LIEBERT, INC
DOI: 10.1089/dia.2020.0387
关键词
Continuous glucose monitoring; Glycemic control; Glycemic variability; Glycemic metrics; Diabetes
The study proposes a robust method to determine the minimum duration of CGM data required for reporting times in ranges and other glycemic metrics, suggesting that certain metrics can be robustly assessed within a 4-week period, while others evaluating hypoglycemia require longer window lengths.
Objective: Consensus continuous glucose monitoring (CGM) guidance includes a recommendation that a minimum of 14 days of CGM data are used to report times in ranges. The previously employed approaches to determine the optimal duration for CGM data have limitations. In this study, we present a robust approach to define the minimum duration of CGM data to report times in ranges, as well as other glycemic metrics. Methods: The approach is based on the median absolute percentage error and employs a sliding time window to reduce the impact of inter-time interval variability, hence allowing smaller data sets to be used. A 10% and 5% threshold were employed to assess the optimal duration of CGM data for a set of commonly employed metrics to assess quality of glycemic control and glycemic variability. To evaluate the impact of the data set size and type of intervention, data from two randomized controlled trials involving participants with type 1 diabetes were used (n = 236 and n = 25). Results: Results suggest that mean glucose reaches the 5% threshold for mean absolute percentage error within 2 weeks, whereas percentage time in target 70-180 mg/dL, mean absolute glucose, standard deviation, and coefficient of variation reach the same threshold within 4 weeks in both data sets, suggesting that these metrics can be robustly assessed from CGM data for a 4-week period, whereas some other metrics require much longer window lengths, especially those evaluating hypoglycemia. Conclusions: Our data suggest that there is no optimal duration for CGM data to robustly assess all outcomes and that the duration required for a robust outcome depends on the population being studied, the sampling frequency, and the primary outcomes selected.
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