Glycaemic variability is associated with coronary artery calcium in men with Type 1 diabetes: the Coronary Artery Calcification in Type 1 Diabetes study

Abstract

Aims-We investigated coronary artery calcium in association with glucose levels and variability measured using continuous glucose monitoring in adults with Type 1 diabetes in the Coronary Artery Calcification in Type 1 Diabetes study.Methods-Coronary artery calcium was measured by electron beam tomography. The presence of any coronary artery calcium was analysed with respect to glucose levels [mean T (mean glucose), % of values < 3.9 mmol/l, > 10 mmol/l and either < 3.9 or > 10 mmol/l] and glycaemic variability [SD T (SD of all glucose values); SD dm (SD of the daily mean glucose levels) and SD hh:mm (glucose SD for a specified time of day, over all days)] using 3-5 days of continuous glucose monitoring from 75 subjects (45 women, 30 men), age 42 ± 9 years (mean ± SD) and diabetes duration of 29 ± 8 years using logistic regression.Results-We observed significant associations between coronary artery calcium and mean T (OR = 4.4, 95% CI 1.1-18.6), % of values > 10 mmol/l (OR = 5.5, 95% CI 1.3-22.6), % of measures < 3.9 or > 10 mmol/l (OR = 5.7, 95% CI 1.3-24.9), SD T (OR = 4.7, 95% CI 1.1-19.7), SD dm (OR = 6.0, 95% CI 1.2-30.4) and SD hh:mm (OR = 4.0, 95% CI 1.1-15.4), among men, but none of these variables were associated with the presence of coronary artery calcium in women.Conclusions-We report the novel finding that subclinical atherosclerosis is associated with glucose levels and variability in men with Type 1 diabetes. The relationship of coronary artery calcium and glucose variability in Type 1 diabetes, and potential gender differences in this association, deserve further study.

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

“…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.…”

Cardiovascular Disease Risk Factors in Youth With Diabetes Mellitus

“…84 Importantly, IR (low GDR) is associated with a more atherogenic fasting lipid profile and lipoprotein subfraction cholesterol distribution and decreased cardiopulmonary fitness and vascular reactivity. 84,[243][244][245] Although long-term data linking IR in T1DM youth to negative long-term cardiovascular outcomes in T1DM adults are lacking, IR correlates with coronary artery calcification, 246 coronary artery disease, and actual cardiovascular events. 154,247 These data argue that IR in T1DM has effects on the cardiovascular system similar to those seen in T2DM.…”

The Challenges of Measuring Glycemic Variability

“…Further, we need to examine which combinations of parameters, with what kind of weighting, will give the best correlation with clinically important events and long-term complications. 11,14,19,23 5. High degree of correlation of different measures of glycemic variability.…”

“…11,19,23 Workers in the field need some time to evaluate and compare the performance of the various measures that have been proposed. This will enable us to examine the correlations among the several measures of variability 13,14 and see if a consensus begins to emerge regarding which is the "best" or "most sensitive" or "more reliable" or "most reproducible" and "easiest to understand" of the various measures. Further, we need to examine which combinations of parameters, with what kind of weighting, will give the best correlation with clinically important events and long-term complications.…”

“…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.…”