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Objective: To evaluate the compliance with self-monitoring of blood glucose (SMBG) and the reliability of diabetes logbooks in women with gestational diabetes mellitus (GDM), as well as the associated determinants and outcomes., Research Design and Methods: We prospectively selected French-speaking women with newly diagnosed GDM who had been referred to our diabetes management program and understood SMBG principles. At the next follow-up visit, we collected SMBG results from glucose meters and logbooks. We analyzed pregnancy outcomes., Results: Data were analyzed over 13 ± 3 days in 91 women. Only 61.5% had performed ≥80% of the required tests. Poor compliance was associated with a family history of diabetes, social deprivation, and non-European origin. The average time between pre- and postprandial tests was 141 ± 20 min, with 46.5% of women performing ≥80% of postprandial measurements 100-140 min after meals. Inadequate timing was associated with ethnicity and higher HbA 1c at baseline. A total of 23.1% of women had <90% matched values in diary and meter memory, and a poor concordance was associated with a family history of diabetes. Poor adherence was associated with more preeclampsia (12.2 vs. 1.9%, P = 0.049), and inadequate postprandial test timing with a higher HbA 1c at delivery (5.3 ± 0.4 vs. 5.0 ± 0.3% [34 ± 2 vs. 31 ± 2 mmol/mol], P < 0.01), despite more frequent insulin therapy., Conclusions: Although women with GDM are considered to be highly motivated, SMBG adherence and reliability are of concern and may be associated with poor gestational prognosis, suggesting that caregivers should systematically check the glucose meter memory to improve GDM management., (© 2017 by the American Diabetes Association.)

Objective: We investigated whether glycation gap (G-Gap), an index of intracellular glycation of proteins, was associated with diabetes complications., Research Design and Methods: We measured concomitantly HbA1c and fructosamine in 925 patients with type 2 diabetes to calculate the G-Gap, defined as the difference between measured HbA1c, and fructosamine-based predicted HbA1c. Patients were explored for retinopathy, nephropathy, peripheral neuropathy, cardiac autonomic neuropathy (n = 512), and silent myocardial ischemia (n = 506)., Results: Macroproteinuria was the only complication that was associated with G-Gap (prevalence in the first, second, and third tertile of G-Gap: 2.9, 6.2, and 11.0%, respectively; P < 0.001). The G-Gap was higher in patients with macroproteinuria than in those without (1.06 ± 1.62 vs. 0.03 ± 1.30%; P < 0.0001). Because HbA1c was associated with both G-Gap (HbA1c 7.0 ± 1.4, 7.9 ± 1.4, and 10.1 ± 1.8% in the first, second, and third G-Gap tertile, respectively; P < 0.0001) and macroproteinuria (HbA1c 8.8 ± 2.2% if macroproteinuria, 8.3 ± 2.0% if none; P < 0.05), and because it could have been a confounder, we matched 54 patients with macroproteinuria and 200 patients without for HbA1c. Because macroproteinuria was associated with lower serum albumin and fructosamine levels, which might account for higher G-Gap, we calculated in this subpopulation albumin-indexed fructosamine and G-Gap; macroproteinuria was independently associated with male sex (odds ratio [OR] 3.2 [95% CI 1.5-6.7]; P < 0.01), hypertension (2.9 [1.1-7.5]; P < 0.05), and the third tertile of albumin-indexed G-Gap (2.3 [1.1-4.4]; P < 0.05) in multivariate analysis., Conclusions: In type 2 diabetic patients, G-Gap was associated with macroproteinuria, independently of HbA1c, albumin levels, and confounding factors, suggesting a specific role of intracellular glycation susceptibility on kidney glomerular changes.

Objective: To evaluate if silent myocardial ischemia (SMI) and silent coronary artery disease (CAD) provide significant additional value to routine cardiovascular risk assessment in type 2 diabetic patients., Research Design and Methods: We followed up to a first cardiovascular event 688 subjects (322 men, aged 59 ± 8 years) out of 731 consecutive asymptomatic type 2 diabetic patients with ≥1 additional risk factor who had been prospectively screened between 1992 and 2006 for SMI by stress myocardial scintigraphy and for silent CAD by coronary angiography., Results: SMI was found in 207 (30.1%) patients and CAD in 76 of those with SMI. Of the patients, 98 had a first cardiovascular event during a 5.4 ± 3.5 (range: 0.1-19.2) year follow-up period. Cox regression analysis considering parameters predicting events but not SMI and CAD ("routine assessment") showed in univariate analyses that macroproteinuria (hazard ratio [HR] 3.33 [95% CI 1.74-6.35]; P < 0.001), current multifactorial care (0.27 [0.15-0.47]; P < 0.001), and peripheral/carotid occlusive arterial disease (PCOAD; 4.33 [2.15-8.71]; P < 0.001) independently predicted cardiovascular events. When added into the model, SMI (HR 1.76 [1.00-3.12]; P = 0.05) and CAD (2.28 [1.24-4.57]; P < 0.01) were also independently associated with events. SMI added to the prediction of an event in the following 5 years above and beyond routine assessment risk prediction (c statistic with or without SMI 0.788 [0.720-0.855] and 0.705 [0.616-0.794], respectively)., Conclusions: Although screening for SMI and silent CAD should not be systematic, these complications are predictive of cardiovascular events in type 2 diabetic patients in addition to routine risk predictors, especially represented by PCOAD, macroproteinuria, and nonintensive management.