Relationships among different glycemic variability indices obtained by continuous glucose monitoring

Yoshifumi Saisho, Chihiro Tanaka, Kumiko Tanaka, Rachel Roberts, Takayuki Abe, Masami Tanaka, Shu Meguro, Junichiro Irie, Toshihide Kawai, Hiroshi Itoh

研究成果: Article

15 引用 (Scopus)

抄録

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.

元の言語English
記事番号424
ページ(範囲)290-296
ページ数7
ジャーナルPrimary Care Diabetes
9
発行部数4
DOI
出版物ステータスPublished - 2015 8 1

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Glycemic Index
Glucose
Hypoglycemia
Tokyo
Type 1 Diabetes Mellitus
Type 2 Diabetes Mellitus
Japan
Physicians

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism
  • Nutrition and Dietetics

これを引用

Relationships among different glycemic variability indices obtained by continuous glucose monitoring. / Saisho, Yoshifumi; Tanaka, Chihiro; Tanaka, Kumiko; Roberts, Rachel; Abe, Takayuki; Tanaka, Masami; Meguro, Shu; Irie, Junichiro; Kawai, Toshihide; Itoh, Hiroshi.

:: Primary Care Diabetes, 巻 9, 番号 4, 424, 01.08.2015, p. 290-296.

研究成果: Article

Saisho, Yoshifumi ; Tanaka, Chihiro ; Tanaka, Kumiko ; Roberts, Rachel ; Abe, Takayuki ; Tanaka, Masami ; Meguro, Shu ; Irie, Junichiro ; Kawai, Toshihide ; Itoh, Hiroshi. / Relationships among different glycemic variability indices obtained by continuous glucose monitoring. :: Primary Care Diabetes. 2015 ; 巻 9, 番号 4. pp. 290-296.
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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.

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