No abstract

There is a growing debate in the literature on whether glucose variability contributes, as well as high HbA1c levels and longstanding diabetes, to the onset and progression of diabetic retinopathy (DR) in patients with diabetes types 1 (DM1) and 2 (DM2). Few data, obtained only by self-monitoring of blood glucose, support this hypothesis. We used continuous glucose monitoring (CGM) to investigate the association between DR and glucose variability parameters (SD, CONGA 2, MAGE), acute hyperglycemia (HBGI) and chronic exposure to glucose (AG and AUC tot). We studied 68 patients from 19 to 69 years old, 35 with DM1 and 33 with DM2. The prevalence of retinopathy was 43 % in DM 1 patients and 39 % in DM 2 patients. The values of all indicators were obtained by CGM for 72 h. DR was diagnosed on direct or indirect ophthalmoscopic examination, after inducing mydriasis with tropicamide. HbA1c was measured at the baseline and 6 weeks after CGM to test the stability of the patients' glycemic control. Univariate analysis showed a close association between DR and duration of diabetes (OR 1.11; 1.04-1.19), intensive insulin therapy (OR 5.6, CI 1.14-27.30), SD (OR 1.03; CI 1.01-1.06) and CONGA 2 (OR 1.02; CI 1.00-1.04)-both indicators of variability and HBGI (OR 1.1, CI 1.01-1.18)-a parameter reflecting acute hyperglycemia. There was no significant correlation with HbA1c (p = 0.070). Multivariate regression analysis showed that disease duration is the parameter most significantly correlating with DR (OR 1.05; 1.01-1.15). These results reinforce the evidence that longstanding disease is the factor most closely associated with DR. Our data also suggest, however, that glucose variability-regardless of HbA1c-may also have a role as a risk factor for DR, particularly in the case of acute fluctuations (as represented by CONGA 2 and SD) and acute hyperglycemia (as represented by HBGI).

Glucose variability has recently been investigated in diabetic patients in several studies, but most of them considered only a few variability indicators and did not systematically correlate them with patients' HbA1c levels and other important characteristics. In thus study, the correlations between HbA1c levels and metabolic control (average glucose, AG), glucose variability (SD, CONGA, MAGE, MODD, BG ROC), hyperglycemia (HBGI), hypoglycemia (LBGI) and postprandial (AUC PP) indices were investigated in patients with type 1 and type 2 diabetes. The study involved 68 patients divided into 3 groups as follows: 35 patients had type 1 diabetes (group 1); 17 had type 2 diabetes and were taking multiple daily injections (MDI) of insulin (group 2); and 16 patients had type 2 diabetes treated with OHA and/or basal insulin (group 3). The indicators were obtained over at least 48 h using a continuous glucose monitoring (CGM) system. HbA1c levels were measured at the baseline and after CGM. HbA1c correlated significantly with AG (r = 0.74), AUC PP (r = 0.69) and HBGI (r = 0.74), but only in type 1 diabetic patients. Patients with longstanding disease and type 1 diabetes had a greater glucose variability, irrespective of their HbA1c levels. Insulin therapy with MDI correlated strongly with HbA1c, but not with glucose variability. HbA1c levels identify states of sustained hyperglycemia and seem to be unaffected by hypoglycemic episodes or short-lived glucose spikes, consequently revealing shortcomings as a "gold standard" indicator of metabolic control. Glucose variability indicators describe the glucose profile of type 1 diabetic patients and identify any worsening glycemic control (typical of longstanding diabetes) more accurately than HbA1c tests.

Continuous glucose monitoring (CGM) gives a unique insight into magnitude and duration of daily glucose fluctuations. Limited data are available on glucose variability (GV) in pregnancy. We aimed to assess GV in healthy pregnant women and cases of type 1 diabetes mellitus or gestational diabetes (GDM) and its possible association with HbA1c. CGM was performed in 50 pregnant women (20 type 1, 20 GDM, and 10 healthy controls) in all three trimesters of pregnancy. We calculated mean amplitude of glycemic excursions (MAGE), standard deviation (SD), interquartile range (IQR), and continuous overlapping net glycemic action (CONGA), as parameters of GV. The high blood glycemic index (HBGI) and low blood glycemic index (LBGI) were also measured as indicators of hyperhypoglycemic risk. Women with type 1 diabetes showed higher GV, with a 2-fold higher risk of hyperglycemic spikes during the day, than healthy pregnant women or GDM ones. GDM women had only slightly higher GV parameters than healthy controls. HbA1c did not correlate with GV indicators in type 1 diabetes or GDM pregnancies. We provided new evidence of the importance of certain GV indicators in pregnant women with GDM or type 1 diabetes and recommended the use of CGM specifically in these populations.

The prevalence of gestational diabetes mellitus is increasing in parallel with the rising prevalence of type 2 diabetes and obesity around the world. Current evidence strongly suggests that women who have had gestational diabetes mellitus are at greater risk of cardiovascular disease later in life. Given the growing prevalence of gestational diabetes mellitus, it is important to identify appropriate reliable markers of cardiovascular disease and specific treatment strategies capable of containing obesity, diabetes, and metabolic syndrome in order to reduce the burden of cardiovascular disease in the women affected.