Key result
Application of the glycemic variability percentage (GVP) to artificial pancreas data revealed an increase in glycemic variability, contrasting with other metrics that suggested a decrease.
Why the study?
Does the glycemic variability percentage (GVP) provide a more accurate assessment of glycemic variability compared to standard metrics in patients using CGM or artificial pancreas systems?
Does the glycemic variability percentage (GVP) provide a more accurate assessment of glycemic variability compared to standard metrics in patients using CGM or artificial pancreas systems?
The GVP, which accounts for both frequency and amplitude of glucose fluctuations, may be a more useful tool than standard deviation for assessing true glycemic variability in CGM and artificial pancreas studies.
Answers are grounded in this paper and cite their sources.
GVP may refine glycemic variability assessment in severe insulin deficiency; leaves open clinical adoption pending larger validation studies.
BACKGROUND: The problem of glycemic variability has been widely acknowledged in patients with diabetes with severe insulin deficiency. In a companion article, we proposed a novel metric, the glycemic variability percentage (GVP), for assessing glycemic variability that accounts for both the amplitude and frequency of glycemic fluctuations. METHOD: We applied the new metric, the GVP, to a previously reported case of a subject using an earlier generation continuous glucose monitoring (CGM) device, in which successive periods of use were associated with an apparent decrease in glycemic variability. Results were compared with histogram distributions for the rate of change of glucose as well. The GVP was also applied to data from a published study of a bihormonal artificial pancreas system comparing results from open loop and closed loop in adolescents and in adults. RESULTS: The GVP was able to quantify the changes in glycemic variability during successive periods of CGM use. Application of the GVP to a published study of a bihormonal artificial pancreas found an increase in glycemic variability compared with other accepted metrics which suggested a decrease in glycemic variability. CONCLUSION: The GVP may be a clinically useful tool in characterizing the change in glycemic variability in subjects using CGM devices. Compared with metrics, such as the standard deviation, that focus solely on the amplitude of oscillations, the GVP, which measures both frequency and amplitude, may also be a more useful tool in assessing the true level of glycemic variability in artificial pancreas studies.
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García et al. (2017) studied Diabetes with severe insulin deficiency. Glycemic variability percentage (GVP) vs. Other accepted metrics (e.g., standard deviation) was evaluated on Glycemic variability. Application of the glycemic variability percentage (GVP) to artificial pancreas data revealed an increase in glycemic variability, contrasting with other metrics that suggested a decrease.
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