Endocrinology and Metabolism

Won Kee Lee (Lee WK)

1 Article

Obesity and Metabolism
A1c Variability Can Predict Coronary Artery Disease in Patients with Type 2 Diabetes with Mean A1c Levels Greater than 7: Eun Ju Lee, You Jeong Kim, Tae Nyun Kim, Tae Ik Kim, Won Kee Lee, Mi-Kyung Kim, Jeong Hyun Park, Byoung Doo Rhee; Endocrinol Metab. 2013;28(2):125-132. Published online June 18, 2013; DOI: https://doi.org/10.3803/EnM.2013.28.2.125

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Background

Recent studies suggested that the association of acute glucose variability and diabetic complications was not consistent, and that A1c variability representing long term glucose fluctuation may be related to coronary atherosclerosis in patients with type 1 diabetes. In this study, we attempt to determine whether or not A1c variability can predict coronary artery disease (CAD) in patients with type 2 diabetes.

Methods

We reviewed data of patients with type 2 diabetes who had undergone coronary angiography (CAG) and had been followed up with for 5 years. The intrapersonal standard deviation (SD) of serially-measured A1c levels adjusted by the different number of assessments among patients (adj-A1c-SD) was considered to be a measure of the variability of A1c.

Results

Among the 269 patients, 121 of them had type 2 diabetes with CAD. In patients with A1c ≥7%, the mean A1c levels and A1c levels at the time of CAG among the three groups were significantly different. The ratio of patients with CAD was the highest in the high adj-A1c-SD group and the lowest in the low adj-A1c-SD group (P=0.017). In multiple regression analysis, adj-A1c-SD was an independent predictor for CAD in subjects with A1c ≥7% (odds ratio, 2.140; P=0.036).

Conclusion

Patients with higher A1c variability for several years showed higher mean A1c levels. A1c variability can be an independent predictor for CAD as seen in angiographs of patients with type 2 diabetes with mean A1c levels over 7%.

Citations

Citations to this article as recorded by

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