No abstract

The 120-minute glycemic index fails to fully account for changes in glycemia after ingestion of a mixed meal because glycemia remains above baseline for a longer period. The CGMS is a convenient method to determine the glucose response/GIs over intervals extended up to 210 minutes, which is adequate time for the absorption of most foods.

Conventional glucometer systems for plasma/blood glucose monitoring are based on colorimetry or static electrochemistry using a fixed input signal. The recent glucometer Linus, Wellion, Agamatrix, USA, based on wavesense dynamic electrochemistry, uses a time-varying input signal to give a more accurate glucose reading. The purpose of this study was to compare the plasma glucose (PG) readings obtained by nursing staff from glucometer Linus and PG values estimated on an approved analyzer Daytona™, Randox, Global Medical Instrumentation, Inc., MN, USA. In the course of 5 weeks, 221 fingerprick capillary blood samples were taken from persons with diabetes at different times and investigated using glucometer Linus. Within two following minutes, blood from the same fingerprick was also collected in a tube and centrifuged; the plasma was analyzed on the Daytona™ analyzer. Statistical analysis was performed using the software SPSS v. 15.0, SPSS Inc., Chicago, IL, USA. A total of 221 paired PG values were plotted on the error grid diagram indicating that 218 values (98.6%) of the glucose readings (Linus vs. Daytona) were within the clinically accurate zone A (maximum difference ±20%) and 3 values (1.4%) within the acceptable zone B. Daytona showed 4 PG values <4.2 mmol/l (75 mg/dl) and their difference of respective Linus readings was always <0.83 mmol/l (15 mg/dl). Correlation of results was strong (r = 0.992). Glucometer Linus readings correspond to the ISO and FDA standards. So, Linus appears to be an accurate device for PG-self-monitoring and clinical practice.

Background: The purpose of this prospective open-label trial was (1) to assess the Influence of oral antidiabetic drugs (OAD) on the glycemic index (GI), glucose response curves (GRCs), daily mean plasma glucose (MPG) and (2) to compare the GI of foods in persons with OAD-treated type 2 diabetes mellitus (T2DM) with the respective GI in healthy persons (HP). Methods: Tested foods containing 50 g of carbohydrates were eaten for breakfast and dinner after 10 and 4 h of fasting, respectively. Glycemic index, GRC, and MPG were obtained using the CGMS® System Gold™ (CGMS). In T2DM patients [n = 16; age (mean ± standard error) 56.0 ± 2.25 years], foods were tested four times: tests 1, 2, and 3 were performed within one week in which placebo was introduced on day 2, and test 4 was carried out five weeks after reintroduction of OAD. Glycemic indexes, GRC, and MPG from tests 1, 2, 3, and 4 were compared. In a control group of 20 HP (age 24.4 ± 0.71 years), the mean GIs were calculated as the mean from 20 subject-related GIs. Results: In T2DM patients, subject-related assessment of GIs, GRC, and MPG distinguished persons with and without OAD effect. Nevertheless, the group-related GIs and the MPG on days 2, 8, and 39 showed no significant difference. There was no significant difference between the GIs in OAD-treated T2DM patients (test 4) versus HP (except in apple baby food). Glucose response curves were significantly larger in T2DM patients (test 4) versus HP. Conclusions: Determination of GRC and subject-related GI using the CGMS appears to be a potential means for the evaluation of efficacy of OAD treatment. Further studies are underway.