No abstract

A self-monitoring disease management strategy, primarily led by diabetes nurses and allowing a timely and efficient use of self-monitoring readings, is able to improve metabolic control, primarily through lifestyle modifications leading to weight loss.

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).

This study evaluates the relation of a Mediterranean dietary pattern and its individual components with the cardiovascular risk factors profile, plasma glucose and body mass index (BMI) in people with type 2 diabetes. We studied 2568 participants at 57 diabetes clinics. Diet was assessed with the EPIC (European Prospective Investigation into Cancer and Nutrition) questionnaire, adherence to the Mediterranean diet was evaluated with the relative Mediterranean diet score (rMED). A high compared to a low score was associated with a better quality of diet and a greater adherence to the nutritional recommendations for diabetes. However, even in the group achieving a high score, only a small proportion of participants met the recommendations for fiber and saturated fat (respectively 17% and 30%). Nonetheless, a high score was associated with lower values of plasma lipids, blood pressure, glycated hemoglobin, and BMI. The relationship of the single food items components of the rMED score with the achievement of treatment targets for plasma lipids, blood pressure, glucose, and BMI were also explored. The study findings support the Mediterranean dietary model as a suitable model for type 2 diabetes and the concept that the beneficial health effects of the Mediterranean diet lie primarily in its synergy among various nutrients and foods rather than on any individual component.

Fetal exposure to glycemic variability and hyperglycemia seems to be important in determining fetal overgrowth in pregnant women with diabetes. Optimal glucose control and less glucose variability are needed as early as possible in both type 1 diabetes and GDM patients to ensure normal fetal growth.

OBJECTIVE -Advanced glycation end products (AGEs), pentosidine and malondialdehyde (MDA), are elevated in type 2 diabetic subjects with coronary and carotid angiopathy. We investigated the relationship of AGEs, MDA, total reactive antioxidant potentials (TRAPs), and vitamin E in type 2 diabetic patients with and without peripheral artery disease (PAD).RESEARCH DESIGN AND METHODS -AGEs, pentosidine, MDA, TRAP, vitamin E, and ankle-brachial index (ABI) were measured in 99 consecutive type 2 diabetic subjects and 20 control subjects.RESULTS -AGEs, pentosidine, and MDA were higher and vitamin E and TRAP were lower in patients with PAD (ABI Ͻ0.9) than in patients without PAD (ABI Ͼ0.9) (P Ͻ 0.001). After multiple regression analysis, a correlation between AGEs and pentosidine, as independent variables, and ABI, as the dependent variable, was found in both patients with and without PAD (r ϭ 0.9198, P Ͻ 0.001 and r ϭ 0.5764, P Ͻ 0.001, respectively) but not in control subjects. When individual regression coefficients were evaluated, only that due to pentosidine was confirmed as significant. For patients with PAD, considering TRAP, vitamin E, and MDA as independent variables and ABI as the dependent variable produced an overall significant regression (r ϭ 0.6913, P Ͻ 0.001). The regression coefficients for TRAP and vitamin E were not significant, indicating that the model is best explained by a single linear regression between MDA and ABI. These findings were also confirmed by principal component analysis. CONCLUSIONS -Resultsshow that pentosidine and MDA are strongly associated with PAD in type 2 diabetic patients.

Diabetes is associated with a greatly increased risk of cardiovascular disease (CVD), which cannot be explained only by known risk factors, such as smoking, hypertension, and atherogenic dyslipidemia, so other factors, such as advanced glycation end-products (AGEs) and oxidative stress, may be involved. In this frame, hyperglycemia and an increased oxidative stress (AGE formation, increased polyol and hexosamine pathway flux, and protein kinase C activation) lead to tissue damage, thus contributing to the onset of cardiovascular complications. Several studies have identified in various cell systems, such as monocytes/macrophages and endothelial cells, specific cellular receptors (RAGE) that bind AGE proteins. The binding of AGEs on RAGE induces the production of cytokines and intracellular oxidative stress, thus leading to vascular damage. Soluble RAGE levels have been identified as hypothetical markers of CVD, but, in this regard, there are sparse and conflicting data in the literature. The purpose of this review was to examine all the available information on this issue with a view to clarifying or at least highlighting the points that are still weak, especially from the point of clinical view.

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.