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Updated: Jun 2, 2026

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Published on: February 24, 2023
Evaluating rate of change as an index of glycemic variability, using continuous glucose monitoring data
Benjamin C Whitelaw1, Pratik Choudhary, David Hopkins
1Department of Diabetic Medicine, Kings College Hospital, NHS Foundation Trust, London, United Kingdom.
Background:
There is no consensus as to the best method to assess glycemic variability from continuous glucose monitoring (CGM) data. Rate of change has been suggested as a preferred method of assessing glycemic variability, but this assertion has not been validated.
Methods:
Forty-eight hours of CGM data were analyzed from 22 subjects (seven controls and 15 with type 1 diabetes) purposively sampled to reflect a range of glycemic variability. SD, mean amplitude of glycemic excursion, continuous overall net glycemic action, SD of rate of change (SDRC), and average absolute rate of change (AARC) were calculated and correlated with a clinical assessment of variability. SDRC and AARC were recalculated following a data smoothing process involving aggregation.
Results:
SDRC calculated from non-aggregated glucose readings gives a weaker correlation (r = 0.66) with the clinical assessment of variability than the correlations obtained by other indices (r = 0.90-0.96). Following a process of data aggregation, to exclude clinically insignificant fluctuations of blood glucose, we demonstrated that 60 min was the optimal aggregation period. The correlation between clinical assessment of variability and SDRC, 60-min aggregated, is 0.93, which is comparable to correlations shown by other established indices. Similar results are obtained for AARC.
Conclusions:
Rate of change calculated after appropriate data aggregation is a valid index of glycemic variability. Optimal data aggregation is achieved by aggregating into 1-h blocks.
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