How Can We Easily Measure Glycemic Variability in Diabetes Mellitus?

Corresponding author: Suk Chon Department of Endocrinology and Metabolism, Kyung Hee University Medical Center, 23 Kyungheedae-ro, Dongdaemun-gu, Seoul 130-872, Korea E-mail: [email protected] Glycemic monitoring is essential for the management of diabetes mellitus. Today, glycosylated hemoglobin (HbA1c) is the most widely used parameter for glycemic monitoring and reflects average glucose levels over 2 to 3 months. However, HbA1c is limited in its ability to reflect short-term glycemic changes. Also, it cannot separately reflect postprandial hyperglycemia (PPH) and fasting hyperglycemia. In addition, HbA1c is a not a good predictor of hypoglycemic episodes as it only accounts for 8% of the probability of severe hypoglycemia [1,2]. A growing body of evidence suggests that PPH and glycemic variability (GV) may be independent risk factors for macrovascular complications in patients with diabetes [3]. The relationship between PPH and cardiovascular disease (CVD) has been consistently reported even in the context of HbA1c levels in the nondiabetic range [4]. Many experimental animal studies indicate that GV, compared with chronic hyperglycemia, promotes excess oxidative stress and worsens cellular and vascular damage [3]. Although the effect of GV on oxidative stress in clinical settings remains controversial, several studies have also confirmed these findings in human studies. Few studies have demonstrated the effect of daily GV on CVD outcomes, although visit-to-visit GV, a longer term index, may predict worse CVD outcome in patients with diabetes. Although GV usually refers to overall glycemic variation including hyper and hypoglycemia, GV is often also used to refer to postprandial glycemic excursion. Complete differentiation between GV and PPH may be impossible because they are correlated with each other, but GV is thought to be important as it is associated with hypoglycemia, especially severe hypoglycemia [5,6]. Severe hypoglycemia can not only directly cause death, but also predict higher risk of mortality, CVD or severe arrhythmia [3]. Especially, patients with type 1 diabetes mellitus (T1DM) are frequently exposed to both excessive hyperglycemia and prolonged, dangerous hypoglycemia even with the availability of insulin pumps and short and long-acting insulin analogs [7]. Thus, clinically, monitoring and minimizing GV is important for preventing hypoglycemia and CVD, in management of diabetes mellitus. There are many measures of GV, extensively reviewed by Rodbard [8]. The most simply used method to assess variability is standard deviation (SD) which is a measure of dispersion of glucose, but its meaning is insufficient in “not” normally distributed data. Mean amplitude of glycemic excursions (MAGE) by Service and colleagues [9], mean of daily differences, and several other measures are commonly used to evaluate GV. However, measurement of GV is challenging because it is still relatively new and most of these measures for GV are calculated from continuous glucose monitoring system (CGMS) [10]. In fact, CGMS is the most reliable and precise method for evaluating GV and PPH. However, it is inconvenient and not easily accessible in general practice. Recently, easily measurable glycemic biomarkers, such as 1,5-anhydroglucitol (1,5-AG), glycated albumin (GA) and fructosamine (FA) have been reported to reflect GV and PPH in T1DM and type 2 diabetes mellitus (T2DM) with various glycemic control status [11-13]. In this issue of Diabetes & Metabolism Journal, Seok et al. [14] reported that 1,5-AG may be a useful marker for assessment of short-term change of glycemic excursion in patients with T1DM. This study showed that the changes of 1,5-AG levels for the period of 2 weeks is negatively correlated with the changes of various CGMS parameter for GV and PPH. Nonetheless, these results are significant only in moderately controlled T1DM with baseline mean CGMS glucose <180 mg/dL and not in poorly conEditorial Clinical Care/Education