Limits...
Clinical Implications of Glucose Variability: Chronic Complications of Diabetes.

Jung HS - Endocrinol Metab (Seoul) (2015)

Bottom Line: However, there remains no generally accepted gold standard for assessing glucose variability.Representative indices for measuring intraday variability include calculation of the standard deviation along with the mean amplitude of glycemic excursions (MAGE).MAGE is used to measure major intraday excursions and is easily measured using continuous glucose monitoring systems.

View Article: PubMed Central - PubMed

Affiliation: Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea. junghs@snu.ac.kr.

ABSTRACT
Glucose variability has been identified as a potential risk factor for diabetic complications; oxidative stress is widely regarded as the mechanism by which glycemic variability induces diabetic complications. However, there remains no generally accepted gold standard for assessing glucose variability. Representative indices for measuring intraday variability include calculation of the standard deviation along with the mean amplitude of glycemic excursions (MAGE). MAGE is used to measure major intraday excursions and is easily measured using continuous glucose monitoring systems. Despite a lack of randomized controlled trials, recent clinical data suggest that long-term glycemic variability, as determined by variability in hemoglobin A1c, may contribute to the development of microvascular complications. Intraday glycemic variability is also suggested to accelerate coronary artery disease in high-risk patients.

No MeSH data available.


Related in: MedlinePlus

Glycemic measures in a randomized controlled trial comparing prandial and basal insulin in patients with cardiovascular disease (HEART2D study). Seven-point mean self-monitoring of blood glucose profiles at baseline (dotted line) and throughout the study (solid line) are indicative of the treatment strategy. Only the change in the mean absolute glucose level, an alleged measure of glucose variability, was significantly different between treatments, with no observable differences in standard deviation or mean amplitude of glycemic excursion. Therefore, accurate interpretation of the relationship between glycemic variability and the endpoint of combined cardiovascular events in this trial is prudent. Adapted from Raz et al. [47], with permission from American Diabetes Association. aP<0.05 between treatment.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4508260&req=5

Figure 3: Glycemic measures in a randomized controlled trial comparing prandial and basal insulin in patients with cardiovascular disease (HEART2D study). Seven-point mean self-monitoring of blood glucose profiles at baseline (dotted line) and throughout the study (solid line) are indicative of the treatment strategy. Only the change in the mean absolute glucose level, an alleged measure of glucose variability, was significantly different between treatments, with no observable differences in standard deviation or mean amplitude of glycemic excursion. Therefore, accurate interpretation of the relationship between glycemic variability and the endpoint of combined cardiovascular events in this trial is prudent. Adapted from Raz et al. [47], with permission from American Diabetes Association. aP<0.05 between treatment.

Mentions: In terms of the DCCT study, the SD was not a predictor of cardiovascular events in patients with T1DM [36]. As for T2DM, some evidence of long-term variability in fasting plasma glucose as a prognostic factor for cardiovascular mortality has been seen in elderly patients [37]. Recent 7-point glucose data from the HEART2D study comparing basal insulin and prandial insulin after acute myocardial infarction (Fig. 3) reported no association between the mean absolute glucose (MAG), an intraday assessment of glucose variability, and the endpoint of combined cardiovascular events [38]. Because neither SD nor MAGE was significantly different between the two treatment groups, this interpretation has been challenged in part due to the reliance on MAG, with no other methods used to assess variability [39]. In the meanwhile, in patients with acute myocardial infarction, MAGE from CGM data collected at the time of admission independently predicted major adverse cardiac events [4041]. A subsequent cross-sectional study also showed that short-term glucose variability, as determined by CGM, was associated with the severity of coronary artery disease [42]. When we look at studies of surrogate endpoints such as subclinical atherosclerosis, more supportive evidence for associations with glucose variability can be found both in T1DM and T2DM [43444546]. However, a substantial proportion of the T2DM studies included mixed populations of patients treated with diet alone, diet and oral antidiabetic medications, and insulin. As such, this may have been a confounding factor in many of the findings, requiring further subgroup analyses to more accurately assess risk factors in this population.


Clinical Implications of Glucose Variability: Chronic Complications of Diabetes.

Jung HS - Endocrinol Metab (Seoul) (2015)

Glycemic measures in a randomized controlled trial comparing prandial and basal insulin in patients with cardiovascular disease (HEART2D study). Seven-point mean self-monitoring of blood glucose profiles at baseline (dotted line) and throughout the study (solid line) are indicative of the treatment strategy. Only the change in the mean absolute glucose level, an alleged measure of glucose variability, was significantly different between treatments, with no observable differences in standard deviation or mean amplitude of glycemic excursion. Therefore, accurate interpretation of the relationship between glycemic variability and the endpoint of combined cardiovascular events in this trial is prudent. Adapted from Raz et al. [47], with permission from American Diabetes Association. aP<0.05 between treatment.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4508260&req=5

Figure 3: Glycemic measures in a randomized controlled trial comparing prandial and basal insulin in patients with cardiovascular disease (HEART2D study). Seven-point mean self-monitoring of blood glucose profiles at baseline (dotted line) and throughout the study (solid line) are indicative of the treatment strategy. Only the change in the mean absolute glucose level, an alleged measure of glucose variability, was significantly different between treatments, with no observable differences in standard deviation or mean amplitude of glycemic excursion. Therefore, accurate interpretation of the relationship between glycemic variability and the endpoint of combined cardiovascular events in this trial is prudent. Adapted from Raz et al. [47], with permission from American Diabetes Association. aP<0.05 between treatment.
Mentions: In terms of the DCCT study, the SD was not a predictor of cardiovascular events in patients with T1DM [36]. As for T2DM, some evidence of long-term variability in fasting plasma glucose as a prognostic factor for cardiovascular mortality has been seen in elderly patients [37]. Recent 7-point glucose data from the HEART2D study comparing basal insulin and prandial insulin after acute myocardial infarction (Fig. 3) reported no association between the mean absolute glucose (MAG), an intraday assessment of glucose variability, and the endpoint of combined cardiovascular events [38]. Because neither SD nor MAGE was significantly different between the two treatment groups, this interpretation has been challenged in part due to the reliance on MAG, with no other methods used to assess variability [39]. In the meanwhile, in patients with acute myocardial infarction, MAGE from CGM data collected at the time of admission independently predicted major adverse cardiac events [4041]. A subsequent cross-sectional study also showed that short-term glucose variability, as determined by CGM, was associated with the severity of coronary artery disease [42]. When we look at studies of surrogate endpoints such as subclinical atherosclerosis, more supportive evidence for associations with glucose variability can be found both in T1DM and T2DM [43444546]. However, a substantial proportion of the T2DM studies included mixed populations of patients treated with diet alone, diet and oral antidiabetic medications, and insulin. As such, this may have been a confounding factor in many of the findings, requiring further subgroup analyses to more accurately assess risk factors in this population.

Bottom Line: However, there remains no generally accepted gold standard for assessing glucose variability.Representative indices for measuring intraday variability include calculation of the standard deviation along with the mean amplitude of glycemic excursions (MAGE).MAGE is used to measure major intraday excursions and is easily measured using continuous glucose monitoring systems.

View Article: PubMed Central - PubMed

Affiliation: Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea. junghs@snu.ac.kr.

ABSTRACT
Glucose variability has been identified as a potential risk factor for diabetic complications; oxidative stress is widely regarded as the mechanism by which glycemic variability induces diabetic complications. However, there remains no generally accepted gold standard for assessing glucose variability. Representative indices for measuring intraday variability include calculation of the standard deviation along with the mean amplitude of glycemic excursions (MAGE). MAGE is used to measure major intraday excursions and is easily measured using continuous glucose monitoring systems. Despite a lack of randomized controlled trials, recent clinical data suggest that long-term glycemic variability, as determined by variability in hemoglobin A1c, may contribute to the development of microvascular complications. Intraday glycemic variability is also suggested to accelerate coronary artery disease in high-risk patients.

No MeSH data available.


Related in: MedlinePlus