A Comparative Study of Eating Habits and Food Intake in Women with Gestational Diabetes according to Early Postpartum Glucose Tolerance Status

BackgroundWomen with gestational diabetes mellitus (GDM) are at high risk for type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD); continuous life-style intervention, especially diet, is central to managing T2DM and CVD. However, little is known about the dietary patterns of women with GDM after delivery. The goal of this study was to compare the eating habits and food intakes of women diagnosed with GDM during the early postpartum period.MethodsWe performed a 75 g oral glucose tolerance test (OGTT) in 184 women with GDM between 6 and 12 weeks after delivery. Based on the results of the OGTT, the subjects were divided into three groups according to the American Diabetes Association criteria; normal glucose tolerance (NGT) (n=100), pre-diabetes (n=73), and diabetes mellitus (DM) (n=11). Eating habits and usual food intake after delivery were investigated using a questionnaire, based on 24 hour-recall, which was administered by a trained dietitian. The daily intake data were analyzed using CAN Pro 3.0. Blood tests were performed pre- and post-delivery.ResultsEating habits were not significantly different among the three groups. However, animal fat consumption was significantly different among the three groups. The intake ratio of fat calories to total calories was also significantly higher in the pre-diabetes and DM groups.ConclusionAlthough diet in the period 6 to 12 weeks postpartum did not influence glucose level, it may be important to educate women with GDM about the risks of excessive animal fat intake during pregnancy and the postpartum period in order to prevent later onset of T2DM

Use of Flash Glucose-Sensing Technology for 12 months as a Replacement for Blood Glucose Monitoring in Insulin-treated Type 2 Diabetes

Introduction: Published evaluations of sensor glucose monitoring use in insulin treated type 2 diabetes are limited. The aim of this study was to assess the impact of flash glucose-sensing technology as a replacement for self-monitoring of blood glucose (SMBG) over a 12-month period in participants with type 2 diabetes who were on intensive insulin therapy. Methods: An open-label, randomized, controlled study in adults with type 2 diabetes on intensive insulin therapy from 26 European diabetes centers aimed at assessing flash glucose sensing technology was conducted. Participants (N = 224) were randomized (1:2 respectively) to a control group (n = 75) that used SMBG (FreeStyle Lite™) or to an intervention group (n = 149) which used sensor glucose data (FreeStyle Libre™ Flash Glucose Monitoring System) for self-management over 6 months. All intervention group participants who completed the 6-month treatment phase continued into an additional 6-month open-access phase. Results: A total of 139 intervention participants completed the 6-month treatment phase and continued into the open-access phase. At 12 months (end of open-access period), time in hypoglycemia [sensor glucose <3.9 mmol/L (70 mg/dL)] was reduced by 50% compared to baseline [−0.70 ± 1.85/24 h (mean ± standard deviation); p = 0.0002]. Nocturnal hypoglycemia [2300 to 0600 hours, <3.9 mmol/L (70 mg/dL)] was reduced by 52%; p = 0.0002. There was no change in time in range [sensor glucose 3.9–10.0 mmol/L (70–180 mg/dL)]. SMBG testing fell from a mean of 3.9 (median 3.9) times/day at baseline to 0.2 (0.0), with an average frequency of sensor scanning of 7.1 (5.7) times/day at 12 months, and mean sensor utilization was 83.6 ± 13.8% (median 88.3%) during the open-access phase. During this 6-month extension period no device-related serious adverse events were reported. Nine participants reported 16 instances of device-related adverse events (e.g. infection, allergy) and 28 participants (20.1%) experienced 134 occurrences of anticipated skin symptoms/sensor-insertion events expected with device use (e.g. erythema, itching and rash). Conclusion: The use of flash glucose-sensing technology for glycemic management in individuals with type 2 diabetes treated by intensive insulin therapy over 12 months was associated with a sustained reduction in hypoglycemia and safely and effectively replaced SMBG. Trial Registration: ClinicalTrials.gov identifier, NCT02082184

Exercise Treadmill Test in Detecting Asymptomatic Coronary Artery Disease in Type 2 Diabetes Mellitus

BackgroundThe present study was designed to develop criteria for screening patients with type 2 diabetes mellitus (T2DM) for asymptomatic coronary artery disease (CAD).MethodsA total of 213 patients with T2DM without typical angina or chest pain were studied between 2002 and 2007. We also evaluated 53 patients with T2DM who had reported chest discomfort using an exercise treadmill test (ETT).ResultsThirty-one of the 213 asymptomatic patients had positive ETT results. We performed coronary angiography on 23 of the 31 patients with a positive ETT and found that 11 of them had significant coronary stenosis. The main differences between the patients with significant stenosis and those with a negative ETT were age (63.1±9.4 vs. 53.7±10.1 years, P=0.008) and duration of diabetes (16.0±7.5 vs. 5.5±5.7 years, P<0.001). The positive predictive value (PPV) of the ETT was calculated to be 47.8%. The PPV of the ETT increased to 87.5% in elderly patients (≥60 years) with a long duration of diabetes (≥10 years). The latter value is similar to that of patients with T2DM who presented with chest discomfort or exertional dyspnea. The PPV of the ETT in symptomatic patients was 76.9%.ConclusionIn the interest of cost-effectiveness, screening for asymptomatic CAD could be limited to elderly patients with a duration of diabetes ≥10 years

Racial/Ethnic Differences in Multiple Self-Care Behaviors in Adults with Diabetes

OBJECTIVE: To assess racial/ethnic differences in multiple diabetes self-care behaviors. DESIGN: Cross-sectional study. PARTICIPANTS: 21,459 participants with diabetes in the 2003 Behavioral Risk Factor Surveillance survey. MEASUREMENTS: The study assessed self-care behaviors including physical activity, fruits/vegetables consumption, glucose testing, and foot examination, as well as a composite of the 4 self-care behaviors across racial/ethnic groups. Multiple logistic regression was used to assess the independent association between race/ethnicity, the composite variable, and each self-care behavior controlling for covariates. STATA was used for statistical analysis. RESULTS: Overall, 6% engaged in all 4 self-care behaviors, with a range of 5% in non-insulin users to 8% in insulin users. Blacks were less likely to exercise (OR 0.63, 95% CI 0.51, 0.79), while Hispanics and “others” were not significantly different from whites. Hispanics (OR 0.64, 95% CI 0.49, 0.82) and others (OR 0.69, 95% CI 0.49, 0.96) were less likely to do home glucose testing, while blacks were not significantly different from whites. Blacks (OR 1.42, 95% CI 1.12, 1.80) were more likely to do home foot examinations, while Hispanics and others were not significantly different from whites. Blacks (OR 0.56, 95% CI 0.36, 0.87) were less likely to engage in all 4 behaviors, while Hispanics and others were not significantly different from whites. There were no significant racial/ethnic differences in fruit and vegetable consumption. CONCLUSIONS: Few patients engage in multiple self-care behaviors at recommended levels, and there are significant racial/ethnic differences in physical activity, dietary, and foot care behaviors among adults with diabetes

How Can We Realize the Clinical Benefits of Continuous Glucose Monitoring?

Controlling glycemia in diabetes remains key to prevent complications in this condition. However, glucose levels can undergo large fluctuations secondary to daily activities, consequently creating management difficulties. The current review summarizes the basics of glucose management in diabetes by addressing the main glycemic parameters. The advantages and limitation of HbA1c, the gold standard measure of glucose control, are discussed together with the clinical importance of hypoglycemia and glycemic variability. The review subsequently moves focus to glucose monitoring techniques in diabetes, assessing advantages and limitations. Monitoring glucose levels is crucial for effective and safe adjustment of hypoglycemic therapy, particularly in insulin users. Self-monitoring of blood glucose (SMBG), based on capillary glucose testing, remains one of the most widely used methods to monitor glucose levels, given the relative accuracy, familiarity, and manageable costs. However, patient inconvenience and the sporadic nature of SMBG limit clinical effectiveness of this approach. In contrast, continuous glucose monitoring (CGM) provides a more comprehensive picture of glucose levels, but these systems are expensive and require constant calibration which, together with concerns over accuracy of earlier devices, restrict CGM use to special groups of patients. The newer flash continuous glucose monitoring (FCGM) system, which is more affordable than conventional CGM devices and does not require calibration, offers an alternative glucose monitoring strategy that comprehensively analyzes glucose profile while sparing patients the inconvenience of capillary glucose testing for therapy adjustment or CGM calibration. The fast development of new CGM devices will gradually displace SMBG as the main glucose testing method. Avoiding the inconvenience of SMBG and optimizing glycemia through alternative glucose testing strategies will help to reduce the risk of complications and improve quality of life in patients with diabetes

Optimizing Postprandial Glycemia in Pediatric Patients With Type 1 Diabetes Using Insulin Pump Therapy: Impact of glycemic index and prandial bolus type

OBJECTIVE—Postprandial glycemic excursions may contribute to the development of diabetes-related complications. Meals of high and low glycemic index (GI) have distinct effects on postprandial glycemia (PPG). Insulin pump therapy offers the potential to tailor insulin delivery to meal composition; however, optimal bolus types for meals of different glycemic loads have not been defined. We sought to compare the impact of GI combined with varying prandial bolus types on PPG