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Glycemic Variability: How Do We Measure It and Why Is It Important?
Sunghwan Suh, Jae Hyeon Kim
Diabetes Metab J. 2015;39(4):273-282.   Published online August 17, 2015
DOI: https://doi.org/10.4093/dmj.2015.39.4.273
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  • 247 Crossref
AbstractAbstract PDFPubReader   

Chronic hyperglycemia is the primary risk factor for the development of complications in diabetes mellitus (DM); however, it is believed that frequent or large glucose fluctuations may independently contribute to diabetes-related complications. Postprandial spikes in blood glucose, as well as hypoglycemic events, are blamed for increased cardiovascular events in DM. Glycemic variability (GV) includes both of these events; hence, minimizing GV can prevent future cardiovascular events. Correcting GV emerges as a target to be pursued in clinical practice to safely reduce the mean blood glucose and to determine its direct effects on vascular complications in diabetes. Modern diabetes management modalities, including glucagon-related peptide-1-based therapy, newer insulins, modern insulin pumps and bariatric surgery, significantly reduce GV. However, defining GV remains a challenge primarily due to the difficulty of measuring it and the lack of consensus regarding the optimal approach for its management. The purpose of this manuscript was not only to review the most recent evidence on GV but also to help readers better understand the available measurement options and how the various definitions relate differently to the development of diabetic complications.

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Original Articles
1,5-Anhydroglucitol as a Useful Marker for Assessing Short-Term Glycemic Excursions in Type 1 Diabetes
Hannah Seok, Ji Hye Huh, Hyun Min Kim, Byung-Wan Lee, Eun Seok Kang, Hyun Chul Lee, Bong Soo Cha
Diabetes Metab J. 2015;39(2):164-170.   Published online March 9, 2015
DOI: https://doi.org/10.4093/dmj.2015.39.2.164
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AbstractAbstract PDFPubReader   
Background

Type 1 diabetes is associated with more severe glycemic variability and more frequent hypoglycemia than type 2 diabetes. Glycemic variability is associated with poor glycemic control and diabetic complications. In this study, we demonstrate the clinical usefulness of serum 1,5-anhydroglucitol (1,5-AG) for assessing changes in glycemic excursion in type 1 diabetes.

Methods

Seventeen patients with type 1 diabetes were enrolled in this study. A continuous glucose monitoring system (CGMS) was applied twice at a 2-week interval to evaluate changes in glycemic variability. The changes in serum glycemic assays, including 1,5-AG, glycated albumin and hemoglobin A1c (HbA1c), were also evaluated.

Results

Most subjects showed severe glycemic excursions, including hypoglycemia and hyperglycemia. The change in 1,5-AG level was significantly correlated with changes in the glycemic excursion indices of the standard deviation (SD), mean amplitude of glucose excursion (MAGE), lability index, mean postmeal maximum glucose, and area under the curve for glucose above 180 mg/dL (r=-0.576, -0.613, -0.600, -0.630, and -0.500, respectively; all P<0.05). Changes in glycated albumin were correlated with changes in SD and MAGE (r=0.495 and 0.517, respectively; all P<0.05). However, changes in HbA1c were not correlated with any changes in the CGMS variables.

Conclusion

1,5-AG may be a useful marker for the assessment of short-term changes in glycemic variability. Furthermore, 1,5-AG may have clinical implications for the evaluation and treatment of glycemic excursions in type 1 diabetes.

Citations

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Is A1C Variability an Independent Predictor for the Progression of Atherosclerosis in Type 2 Diabetic Patients?
Chul Sik Kim, So Young Park, Sung Hoon Yu, Jun Goo Kang, Ohk Hyun Ryu, Seong Jin Lee, Eun Gyung Hong, Hyeon Kyu Kim, Doo-Man Kim, Jae Myung Yoo, Sung Hee Ihm, Moon Gi Choi, Hyung Joon Yoo
Korean Diabetes J. 2010;34(3):174-181.   Published online June 30, 2010
DOI: https://doi.org/10.4093/kdj.2010.34.3.174
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AbstractAbstract PDFPubReader   
Background

Little is known about the relative contribution of long-term glycemic variability to the risk of macrovascular complications in type 2 diabetes. This study was conducted to evaluate the effect of A1C variability on the progression of carotid artery intima-media thickness (IMT) in type 2 diabetic patients.

Methods

Among type 2 diabetic patients who visited Hallym University Sacred Heart Hospital from March 2007 to September 2009, 120 patients who had carotid artery IMT measured annually and A1C checked every three months for at least one year were analyzed. Individual A1C variability was defined as the standard deviation (SD) of five A1C levels taken every three months for approximately one year. Change in IMT was defined as an increase in IMT on follow-up measurement. The association between the SD of A1C and changes in IMT was evaluated.

Results

With greater A1C variability, there was a greater increase in the mean IMT (r = 0.350, P < 0.001) of the carotid artery. After adjusting for confounding factors that may influence IMT, A1C variability was significantly associated with the progression of IMT (r = 0.222, P = 0.034). However, the SD of A1C was not a significant independent risk factor for the progression of IMT in multiple regression analysis (β = 0.158, P = 0.093).

Conclusion

Higher A1C variability is associated with IMT progression in type 2 diabetic patients; however, it is not an independent predictor of IMT progression. Overall glycemic control is the most important factor in the progression of IMT.

Citations

Citations to this article as recorded by  
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