A new approach for investigating the relative contribution of basal glucose and postprandial glucose to HbA1C

To develop an accurate method for evaluating the relative contributions of basal glucose (BG) and postprandial glucose (PPG) to glycated haemoglobin (HbA1c) in subjects with hyperglycaemia using a Continuous Glucose Monitoring System (CGMS®). The subjects were divided into the normal glucose tolerance (NGT), impaired glucose tolerance (IGT), newly-diagnosed type 2 diabetes (NDDM), and drug-treated type 2 diabetes (T2DM) groups. We evaluated the relative contributions of BG and PPG to HbA1c in patients with hyperglycaemia according to three different baseline values. Subjects (n = 490) were grouped as follows: 92 NGT, 36 IGT, 131 NDDM, and 231 T2DM. The relative contributions of PPG to HbA1c were calculated using baseline values of 6.1 mmol/L, 5.6 mmol/L, and the 24-h glucose curve of the NGT group. The relative contribution of PPG to HbA1c decreased progressively from the IGT group to the T2DM group. Compared with the 24-h glucose curve as the baseline, the relative contribution of PPG was overestimated in 9.04% and 1.76% of the subjects when 6.1 mmol/L and 5.6 mmol/L were used as baselines, respectively (P < 0.01), in T2DM patients. The 24-h glucose curve of NGT is more suitable for studying the relative contributions of BG and PPG to HbA1c and it is more precise, as it considers physiological fluctuations in NGT after meals. However, 5.6 mmol/L can be used when the 24-h glucose curve for NGT is unavailable; using 6.1 mmol/L as a baseline value may overestimate the contribution to the HbA1c. There is no unified standard for assessing the contributions of basal glucose (BG) and postprandial glucose (PPG) to HbA1c. The 24-h glucose curve of NGT is more suitable for studying the relative contributions of BG and PPG to HbA1c, as it considers physiological fluctuations in NGT after meals. However, 5.6 mmol/L can be used when the 24-h glucose curve for NGT is unavailable; using 6.1 mmol/L as a baseline value may overestimate the contribution to the HbA1c.

Functionality of Djulis (Chenopodium formosanum) By-Products and In Vivo Anti-Diabetes Effect in Type 2 Diabetes Mellitus Patients

Djulis (Chenopodium formosanum Koidz.) is a species of cereal grain native to Taiwan. It is rich in dietary fibre and antioxidants and therefore reputed to relieve constipation, suppress inflammation, and lower blood glucose. The aim of this study was to investigate the composition and physicochemical properties of dietary fibre from djulis hull. Meanwhile, determination of the in vivo antidiabetic effect on patients with type 2 diabetes mellitus (T2DM) after consuming the djulis hull powder. Djulis hull contained dietary fibre 75.21 ± 0.17% dry weight, and insoluble dietary fibre (IDF) reached 71.54 ± 0.27% dry weight. The IDF postponed the adsorption of glucose and reduced the activity of α-amylase. Postprandial blood glucose levels in patients with T2DM showed three different tendencies. First, the area under the glucose curve was significantly lower after ingesting 10 or 5 g djulis hull powder, which then postponed the adsorption of glucose, but the area under the glucose curve was similar with the two doses. After consuming 10 g djulis hull before 75 g glucose 30 and 60 min after the meal, patients with T2DM had blood glucose values that were significantly lower at the same postprandial times than those of patients who did not consume djulis hull. In short, patients who consumed djulis hull prior to glucose administration had decreased blood glucose level compared with those who did not. Djulis hull may have benefits for patients with T2DM.

Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes: An IMI-DIRECT study

Aim Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D. Methods The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders. Results At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1–3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18–1.92) for subgroup 2 and 1.88 (-0.08–3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose. Conclusions Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk.

Glycaemic responses to glucose and rice in people of Chinese and European ethnicity

Aims: Diabetes rates are especially high in China. Risk of Type 2 diabetes increases with high intakes of white rice, a staple food of Chinese people. Ethnic differences in postprandial glycaemia have been reported. We compared glycaemic responses to glucose and five rice varieties in people of European and Chinese ethnicity and examined possible determinants of ethnic differences in postprandial glycaemia. Methods: Self-identified Chinese (n = 32) and European (n = 31) healthy volunteers attended on eight occasions for studies following ingestion of glucose and jasmine, basmati, brown, Doongara® and parboiled rice. In addition to measuring glycaemic response, we investigated physical activity levels, extent of chewing of rice and salivary α-amylase activity to determine whether these measures explained any differences in postprandial glycaemia. Results: Glycaemic response, measured by incremental area under the glucose curve, was over 60% greater for the five rice varieties (P < 0.001) and 39% greater for glucose (P < 0.004) amongst Chinese compared with Europeans. The calculated glycaemic index was approximately 20% greater for rice varieties other than basmati (P = 0.01 to 0.05). Ethnicity [adjusted risk ratio 1.4 (1.2-1.8) P < 0.001] and rice variety were the only important determinants of incremental area under the glucose curve. Conclusions: Glycaemic responses following ingestion of glucose and several rice varieties are appreciably greater in Chinese compared with Europeans, suggesting the need to review recommendations regarding dietary carbohydrate amongst rice-eating populations at high risk of diabetes. © 2012 Diabetes UK.

Glycaemic responses to glucose and rice in people of Chinese and European ethnicity

Aims: Diabetes rates are especially high in China. Risk of Type 2 diabetes increases with high intakes of white rice, a staple food of Chinese people. Ethnic differences in postprandial glycaemia have been reported. We compared glycaemic responses to glucose and five rice varieties in people of European and Chinese ethnicity and examined possible determinants of ethnic differences in postprandial glycaemia. Methods: Self-identified Chinese (n = 32) and European (n = 31) healthy volunteers attended on eight occasions for studies following ingestion of glucose and jasmine, basmati, brown, Doongara® and parboiled rice. In addition to measuring glycaemic response, we investigated physical activity levels, extent of chewing of rice and salivary α-amylase activity to determine whether these measures explained any differences in postprandial glycaemia. Results: Glycaemic response, measured by incremental area under the glucose curve, was over 60% greater for the five rice varieties (P < 0.001) and 39% greater for glucose (P < 0.004) amongst Chinese compared with Europeans. The calculated glycaemic index was approximately 20% greater for rice varieties other than basmati (P = 0.01 to 0.05). Ethnicity [adjusted risk ratio 1.4 (1.2-1.8) P < 0.001] and rice variety were the only important determinants of incremental area under the glucose curve. Conclusions: Glycaemic responses following ingestion of glucose and several rice varieties are appreciably greater in Chinese compared with Europeans, suggesting the need to review recommendations regarding dietary carbohydrate amongst rice-eating populations at high risk of diabetes. © 2012 Diabetes UK.

The Diagnostic Value of the Glucose Curve in Individuals with and without Diabetes

Aim: Of this study is to demonstrate the importance of glucose curve test in monitoring pre and post-meal variation in diabetic and normal individuals. Methodology: The individuals subjected to this study mainly grouped in two categories the (DM2 group) and the (Control group), they instructed to came fasting at which blood sample will be collected in EDTA and blank tube then after 30 min. the first post-prandial blood sample collected and then after every 1,2,3,4,5,6,7,8 hours blood sample collected subsequently, then serum separated from each sample (except the EDTA tube) analysed biochemically for glucose and glycated haemoglobin HbA1c (from EDTA tube). Result: We found that, the calculated glucose based on mean glycated haemoglobin HbA1c% results underestimate the real concentrations all over the glucose curve in control group but in DM2 group it underestimate the mean and some actually measured concentration in some points of the curve which adds more burden on the diabetic patient and the responsibility of adjusting the dose and time of administration. Conclusion: from our prospect we recommend the use of blood glucose curve as a monitoring and diagnostic tool generally for glucose metabolism in normal, pre-diabetic, diabetic and uncontrolled diabetic patients before and during therapeutic conditions.

Restricting carbohydrates at breakfast is sufficient to reduce 24-hour exposure to postprandial hyperglycemia and improve glycemic variability

ABSTRACT Background The breakfast meal often results in the largest postprandial hyperglycemic excursion in people with type 2 diabetes. Objective Our purpose was to investigate whether restricting carbohydrates at breakfast would be a simple and feasible strategy to reduce daily exposure to postprandial hyperglycemia. Design Adults with physician-diagnosed type 2 diabetes [n = 23; mean ± SD age: 59 ± 11 y; glycated hemoglobin: 6.7% ± 0.6%; body mass index (kg/m2): 31 ± 7] completed two 24-h isocaloric intervention periods in a random order. Participants consumed one of the following breakfasts: 1) a very-low-carbohydrate high-fat breakfast (LCBF; <10% of energy from carbohydrate, 85% of energy from fat, 15% of energy from protein) or 2) a breakfast with dietary guidelines–recommended nutrient profile (GLBF; 55% of energy from carbohydrate, 30% of energy from fat, 15% of energy from protein), with the same lunch and dinner provided. Continuous glucose monitoring was used to assess postprandial glucose responses over 24 h, and visual analog scales were used to assess ratings of hunger and fullness. Results The LCBF significantly reduced postprandial hyperglycemia after breakfast (P < 0.01) and did not adversely affect glycemia after lunch or dinner. As such, overall postprandial hyperglycemia (24-h incremental area under the glucose curve) and glycemic variability (mean amplitude of glycemic excursions) were reduced with the LCBF (24-h incremental area under the glucose curve: −173 ± 361 mmol/L; P = 0.03; mean amplitude of glycemic excursions: −0.4 ± 0.8 mmol/L · 24 h; P = 0.03) compared with the GLBF. Premeal hunger was lower before dinner with the LCBF than with the GLBF (P-interaction = 0.03). Conclusions A very-low-carbohydrate high-fat breakfast lowers postbreakfast glucose excursions. The effects of this simple strategy appear to be sufficient to lower overall exposure to postprandial hyperglycemia and improve glycemic variability. Longer-term interventions are warranted. This trial was registered at clinicaltrials.gov as NCT02982330.

Therapy Adjustments Based on Trend Arrows Using Continuous Glucose Monitoring Systems

Continuous glucose monitoring (CGM) systems use trend arrows to accurately display the anticipated glucose curve for the user. These are used for both “real-time” glucose monitoring and for intermittent scanning glucose monitoring. Trend arrow data are used by people with diabetes to make corrections to their glucose control. It is essential that they are correctly interpreted when adjusting insulin doses and to ensure that appropriate treatment decisions are made. The aim of this article is to provide general treatment guidance for diabetes teams and for people with diabetes using CGM in the context of trend arrows. This is based on previous recommendations for interpreting trend arrows without losing sight of the need for individual therapy adjustment.