TY - JOUR
T1 - Relationships among different glycemic variability indices obtained by continuous glucose monitoring
AU - Saisho, Yoshifumi
AU - Tanaka, Chihiro
AU - Tanaka, Kumiko
AU - Roberts, Rachel
AU - Abe, Takayuki
AU - Tanaka, Masami
AU - Meguro, Shu
AU - Irie, Junichiro
AU - Kawai, Toshihide
AU - Itoh, Hiroshi
N1 - Publisher Copyright:
© 2014 Primary Care Diabetes Europe.
PY - 2015/8/1
Y1 - 2015/8/1
N2 - Abstract 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.
AB - Abstract 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.
KW - Continuousglucosemonitoring
KW - Diabetesmellitus
KW - Glycemicvariability
KW - Standarddeviation
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U2 - 10.1016/j.pcd.2014.10.001
DO - 10.1016/j.pcd.2014.10.001
M3 - Article
C2 - 25456706
AN - SCOPUS:84937632531
SN - 1751-9918
VL - 9
SP - 290
EP - 296
JO - Primary Care Diabetes
JF - Primary Care Diabetes
IS - 4
M1 - 424
ER -
