Literature DB >> 25456706

Relationships among different glycemic variability indices obtained by continuous glucose monitoring.

Yoshifumi Saisho1, Chihiro Tanaka2, Kumiko Tanaka2, Rachel Roberts3, Takayuki Abe3, Masami Tanaka2, Shu Meguro2, Junichiro Irie2, Toshihide Kawai2, Hiroshi Itoh2.   

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.
Copyright © 2014 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Continuous glucose monitoring; Diabetes mellitus; Glycemic variability; Standard deviation

Mesh:

Substances:

Year:  2014        PMID: 25456706     DOI: 10.1016/j.pcd.2014.10.001

Source DB:  PubMed          Journal:  Prim Care Diabetes        ISSN: 1878-0210            Impact factor:   2.459


  15 in total

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Journal:  J Diabetes Sci Technol       Date:  2018-02-16

7.  Glycemic Variability Assessment with a 14-Day Continuous Glucose Monitoring System: When and How Long to Measure MAGE (Mean Amplitude of Glucose Excursion) for Optimal Reliability?

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Journal:  J Diabetes Sci Technol       Date:  2021-02-10

8.  1,5-Anhydro-D-Glucitol Could Reflect Hypoglycemia Risk in Patients with Type 2 Diabetes Receiving Insulin Therapy.

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9.  Long-term Effect of Islet Transplantation on Glycemic Variability.

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Review 10.  Devices for continuous monitoring of glucose: update in technology.

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Journal:  Med Devices (Auckl)       Date:  2017-09-12
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