Relationships among different glycemic variability indices obtained by continuous glucose monitoring

• Glycemic variability indices correlate each other with r value of 0.5–0.8.
• ICG, MODD, CONGA1 and MAGE are more strongly relates to SD than mean glucose.
• Glycemic variability indices moderately relate to hypoglycemia.
• Combination of mean and SD glucose is useful for predicting hypoglycemia.

The aim of this study was to assess the relationships among indices of glycemic variability obtained by continuous glucose monitoring (CGM). CGM was performed in 88 patients with diabetes (20 type 1 and 68 type 2 diabetes, age 59 ± 15 years) admitted to our hospital (Keio University Hospital, Tokyo, Japan) between 2010 and 2012. Mean glucose, glucose standard deviation (SDglu) and other glycemic indices such as index of glycemic control (ICG), J-index, mean of daily differences (MODD), continuous overlapping net glycemic action 1 (CONGA1), mean amplitude of glycemic excursions (MAGE) and M value were calculated from CGM data, and the correlations among these indices were assessed. There were strong correlations between SDglu and the indices MAGE, CONGA1, MODD and M value (all r > 0.8, P < 0.05). On the other hand, mean glucose was strongly correlated with J index and M value (both r > 0.8, P < 0.05). SDglu and other glycemic variability indices were more strongly correlated with hypoglycemia than was mean glucose, and the combination of mean glucose and SDglu was useful for predicting hypoglycemia in patients with diabetes. In this study, we demonstrated the characteristics of various glycemic variability indices in relation to mean glucose and SDglu. This information will help physicians to understand the characteristics of various glycemic variability indices and to select an appropriate index for their purpose. Our results also underpin the importance of glycemic variability in relation to risk of hypoglycemia in patients with diabetes.