A Decrease in Glucose Variability Does Not Reduce Cardiovascular Event Rates in Type 2 Diabetic Patients After Acute Myocardial Infarction

Siegelaar, Sarah E.; Kerr, Lisa; Jacober, Scott J.; DeVries, J. Hans

doi:10.2337/dc10-1684

Cited by 85 publications

(70 citation statements)

References 11 publications

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“…Of note, previous reports suggested that acute oscillations of blood glucose have a more deleterious effect on endothelial function than constant hyperglycemia in patients with type 2 diabetes (T2DM) (3,4), which may support the concept that glycemic variability can induce oxidative stress and thereby affect the pathophysiologic pathways through which diabetes complications arise (5). However, although some studies have reported that increased glycemic variability may be associated with the incidence of diabetic retinopathy (6,7), diabetic neuropathy (8), and coronary artery calcification (9) in patients with T2DM and type 1 diabetes (T1DM), other studies have not supported this association (10)(11)(12). Nevertheless, although its relevance to vascular complications remains uncertain (13), at a given level of glycemia, increased glucose variability raises the risk of hypoglycemia (14)(15)(16) and, hence, is clinically important.…”

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confidence: 63%

Glycemic Variability in Patients With Early Type 2 Diabetes: The Impact of Improvement in β-Cell Function

et al. 2014

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OBJECTIVEIncreased glycemic variability has been reported to be associated with the risk of hypoglycemia and possibly diabetes complications and is believed to be due to b-cell dysfunction. However, it is not known whether improvement in b-cell function can reduce glycemic variability. Because short-term intensive insulin therapy (IIT) can improve b-cell function in early type 2 diabetes (T2DM), our objective was to determine whether the b-cell functional recovery induced by this therapy is associated with decreased glycemic variability. RESEARCH DESIGN AND METHODSSixty-one patients with T2DM of 3.0 years mean duration underwent 4 weeks of IIT, which consisted of basal insulin detemir and premeal insulin aspart. Glucose variability was assessed in both the first and the last week by the coefficient of variation of capillary glucose on daily 6-point self-monitoring profiles. b-Cell function before and after IIT was assessed with the Insulin Secretion-Sensitivity Index-2 (ISSI-2). RESULTSBetween the first and the last week on IIT, 55.7% of patients had a reduction in glucose variability. Change in glucose variability was negatively correlated with the change in b-cell function (ISSI-2) (r = 20.34, P = 0.008). On multiple linear regression analyses, percentage change in ISSI-2 emerged as the only factor independently associated with the change in glucose variability (standardized b = 20.42, P = 0.03). Moreover, patients with an increase in ISSI-2 ‡25% experienced a reduction in glucose variability compared with their peers who had almost no change (20.041 6 0.06 vs. 20.0002 6 0.04, respectively; P = 0.006). CONCLUSIONSIn early T2DM, glycemic variability is a modifiable parameter that can be reduced by improving b-cell function with short-term IIT.

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confidence: 63%

Glycemic Variability in Patients With Early Type 2 Diabetes: The Impact of Improvement in β-Cell Function

et al. 2014

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“…The study was discontinued prematurely, however, due to too few CVD events and less-than-expected differences in postprandial glucose values. The HEART2D data were reanalyzed to evaluate if GV had an effect on cardiovascular outcomes (11). Only one of three markers of GV was reduced with the prandial-targeted therapy and this was the newest, least established GV marker.…”

Section: Dwilliam T Cefalu Editor In Chief Diabetes Carementioning

confidence: 99%

Glycemic Variability and Diabetes Complications: Does It Matter? Simply Put, There Are Better Glycemic Markers!

Bergenstal

2015

Diabetes Care

116

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There is no argument that improving mean levels of glycemic control as judged by assays for glycated hemoglobin (HbA1c) reduces the risks of microvascular complications and cardiovascular disease events in patients with type 1 and type 2 diabetes. However, observations in some trials have suggested that targeting HbA1c to suggested targets may not always result in improved outcomes for people with long-standing type 2 diabetes. The reasons why the glycemic control strategies that primarily use HbA1c in these studies did not have predicted outcomes are not clear. Thus, controversy remains as to whether there are glycemic metrics beyond HbA1c that can be defined as effective measures that can be used in addition to HbA1c to help in assessing the risk of an individual developing diabetes complications. In this regard, the concept of “glycemic variability” (GV) is one metric that has attracted a lot of attention. GV can be simply defined as the degree to which a patient’s blood glucose level fluctuates between high (peaks) and low (nadir) levels. The best and most precise way to assess GV is also one that is still debated. Thus, while there is universal agreement that HbA1c is the current gold standard for the primary clinical target, there is no consensus as to whether other proposed glycemic metrics hold promise to provide additional clinical data or whether there should be additional targets beyond HbA1c. Therefore, given the current controversy, we provide a Point-Counterpoint debate on this issue. In the preceding point narrative, Dr. Hirsch provides his argument that fluctuations in blood glucose as assessed by GV metrics are deleterious and control of GV should be a primary treatment target. In the counterpoint narrative below, Dr. Bergenstal argues that there are better markers to assess the risk of diabetes than GV and provides his consideration of other concepts. —William T. Cefalu Editor in Chief, Diabetes Care

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“…We are now blessed with a multiplicity of measures of glycemic variability. These include SD, coefficient of variation (CV), interquartile range, MAGE, MODD, mean absolute glucose (MAG) change per hour, and several subtypes of the SD, [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] including total SD (SD T ), SD within days (SD w ), between daily means (SD dm ), between days (SD b ), between days after correction for variability in daily means (SD b // dm ), variability by time of day for the mean glucose profile from several days (SD hh:mm ), measures of the stability of the glycemic profile or similarity of glucose patterns from day to day (root mean square error), [17][18][19] a "distance travelled" 20 that is closely related to the MAG rate of change, 21 glucose fluctuation as defined by Mori and associates, 22 and combinations of several of these measures. 11,19,23 Workers in the field need some time to evaluate and compare the performance of the various measures that have been proposed.…”

Section: The Magnitude Of Glycemic Variability Is Highlymentioning

confidence: 99%

The Challenges of Measuring Glycemic Variability

Rodbard¹

2012

J Diabetes Sci Technol

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Abbreviations: (CGM) continuous glucose monitoring, (CV) coefficient of variation, (GRADE) glycemic risk assessment diabetes equation, (MAD) mean absolute difference, (MAG) mean absolute glucose rate of change, (MAGE) mean amplitude of glucose excursion, (MODD) mean of daily differences, (SD) standard deviation, (SEM) standard error of the mean, (SMBG) self-monitoring of blood glucose AbstractThis commentary reviews several of the challenges encountered when attempting to quantify glycemic variability and correlate it with risk of diabetes complications. These challenges include (1) immaturity of the field, including problems of data accuracy, precision, reliability, cost, and availability; (2) larger relative error in the estimates of glycemic variability than in the estimates of the mean glucose; (3) high correlation between glycemic variability and mean glucose level; (4) multiplicity of measures; (5) correlation of the multiple measures; (6) duplication or reinvention of methods; (7) confusion of measures of glycemic variability with measures of quality of glycemic control; (8) the problem of multiple comparisons when assessing relationships among multiple measures of variability and multiple clinical end points; and (9) differing needs for routine clinical practice and clinical research applications.

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A Decrease in Glucose Variability Does Not Reduce Cardiovascular Event Rates in Type 2 Diabetic Patients After Acute Myocardial Infarction

Cited by 85 publications

References 11 publications

Glycemic Variability in Patients With Early Type 2 Diabetes: The Impact of Improvement in β-Cell Function

Glycemic Variability in Patients With Early Type 2 Diabetes: The Impact of Improvement in β-Cell Function

Glycemic Variability and Diabetes Complications: Does It Matter? Simply Put, There Are Better Glycemic Markers!

The Challenges of Measuring Glycemic Variability

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