1,5-anhydroglucitol的2型糖尿病患者的血糖波动之间的相关性

Chinese Medical Journal 2011;124(22):3641-3645 3641

Original article

Correlation between 1,5-anhydroglucitol and glycemic excursions in type 2 diabetic patients

SUN Jie, DOU Jing-tao, WANG Xian-ling, YANG Guo-qing, LÜ Zhao-hui, ZHENG Hua, MA Fang-ling, LU Ju-ming and MU Yi-ming

Keywords: 1,5-anhydroglucitol; type 2 diabetes mellitus; glycemic excursions

Background The accurate and comprehensive assessment of glycemic control in patients with diabetes is important for optimizing glycemic management and for formulating personalized diabetic treatment schemes. This study aimed to analyze the correlation between 1,5-anhydroglucitol (1,5-AG) and glycemic excursions in type 2 diabetic patients.

Methods Seventy-one outpatients with type 2 diabetes mellitus were randomly recruited from Chinese People’s Liberation Army General Hospital. Using a continuous glucose monitoring system (CGMS), these patients’ blood glucose levels were monitored for three consecutive days to obtain mean blood glucose (MBG) data. Intraday glycemic excursions were evaluated using the mean amplitude of glycemic excursions (MAGE), the largest amplitude of glycemic excursions (LAGE), standard deviation of blood glucose (SDBG) and the M-value. Interday glycemic excursion was assessed by absolute mean of daily difference (MODD). Postprandial glycemic fluctuations were evaluated using postprandial glucose excursions (PPGE) and postprandial incremental area under the curve (iAUC). Fasting venous blood samples were collected to measure serum 1,5-AG, whole-blood hemoglobin A1c (HbA1c) and serum glycated albumin (GA). Clinical markers of glycemia and parameters of glycemic excursions from CGMS were analyzed using the Pearson correlation coefficient and multivariate stepwise regression.

Results Pearson correlation analysis revealed that 1,5-AG was significantly correlated with MAGE, SDBG, M-value, LAGE, PPGE and iAUC (r values were –0.509, –0.430, –0.530, –0.462, –0.416 and –0.435, respectively, P <0.01), especially in moderately and well-controlled patients, based on defined HbA1c levels. Multivariate stepwise regression analysis revealed a negative correlation between 1,5-AG and the above parameters, but not HbA1c and GA. Finally, HbA1c and GA were positively correlated with MBG and fasting blood glucose (FBG).

Conclusions 1,5-AG was much better than HbA1c and GA as a marker of glycemic excursions in type 2 diabetic patients. Based on these results 1,5-AG is the best metric for assessing postprandial glucose levels in moderately and well-controlled patients, while HbA1c and GA were superior to 1,5-AG for monitoring MBG and FBG.

Chin Med J 2011;124(22):3641-3645

hree key elements of glucose metabolic disturbance are fasting hyperglycemic state, postprandial chronic hyperglycemic state and changes in glycemic excursions.1 Chronic hyperglycemia increases the risk of developing diabetic complications. In vitro experiments showed that damage to the vascular endothelium by periodical glycemic excursions is probably more serious than chronic hyperglycemia.2 Furthermore, previous studies suggested postprandial glucose could predict more strongly mortality for all causes and cardiovascular than fasting blood glucose (FBG).3,4 Therefore, the accurate and comprehensive assessment of glycemic control conditions, especially the characteristics of glycemic excursions in patients with diabetes, are of great significance for optimizing glycemic management and formulating personalized treatment schemes. The “gold standard” of blood glucose monitoring, hemoglobin A1c (HbA1c) levels, is frequently used in a number of large-scale prospective studies to evaluate persistent hyperglycemia and correlations with the risk of a variety of chronic complications.3,5,6 It has recently been shown that postprandial hyperglycemia and glycemic excursions are also closely correlated with diabetic angiopathy. In

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the past, measuring blood glucose levels at multiple times throughout a single day via self-monitoring blood glucose (SMBG) was generally used to evaluate the effects of postprandial hyperglycemia on variations in blood glucose levels; however, this method cannot accurately reflect peaks and valleys in blood glucose levels since these values are limited to specific time points. Although the continuous glucose monitoring system (CGMS) is regarded as the “gold standard” for analyzing glycemic

Department of Endocrinology, Chinese People’s Liberation Army General Hospital, Beijing 100853, China (Sun J, Dou JT, Wang XL, Yang GQ, Lü ZH, Zheng H, Ma FL, Lu JM and Mu YM)

Correspondence to: Prof. DOU Jing-tao, Department of Endocrinology, Chinese People’s Liberation Army General Hospital, Beijing 100853, China (Tel: 86-10-66937711. Fax: 86-10-68168631. Email: jingtaodou@http://www.51wendang.com)

SUN Jie is now working at Department of Endocrinology, Chinese People’s Liberation Army 89th Hospital, Weifang, Shandong 261041, China.

This study was supported by a grant from diabetes drug clinical research and innovation of the new drug evaluation technology standardization system research from Chinese Ministry of Science and Technology (No. 2008ZX09312-006).

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