Glucose concentrations in blood and tissue - a pilot study on variable time lag.

AIM: The aim of this pilot study was to acquire insight into the parameters of glycaemic control, especially, (1) the time delay (lag phase) between plasma and tissue glucose concentrations in relation to rise and fall in glucose levels and (2) the rate of glucose increase and decrease. METHODS: Four healthy people (HP), 4 people with type 1diabetes (DM1) and 4 with type 2 diabetes (DM2) underwent concurrent glucose measurements by means of (1) the continuous glucose monitoring system (CGMS-Medtronic), Medtronic-Minimed, CA, USA, calibrated by the glucometer Calla, Wellion, Austria, and, (2) the Beckman II analyser to measure glucose concentrations in venous plasma. Samples were taken on 4 consecutive days in the fasting state and 4 times after consumption of 50 g glucose. Carelink Personal, MS Excel, Maple and Mat lab were applied to plot the evolution of glucose concentration and analyse the results. The time difference between increase and decrease was calculated for HP, DM 1 and DM 2. RESULTS: In DM1and DM2, glucose tolerance testing (GTT) resulted in slower transport of glucose into subcutaneous tissue than in HP where the lag phase lasted up to 12 min. The maximum increase/decrease rates in DM1 and DM2 vs HP were 0.25 vs < 0.1 mmol/L/min. CONCLUSION: CGMS is shown to provide reliable plasma glucose concentrations provided the system is calibrated during a steady state. The analysis of glucose change rates improves understanding of metabolic processes better than standard GTT.

Wavesense technology glucometer Linus for routine self-monitoring and clinical practice.

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.

Influence of oral antidiabetic drugs on hyperglycemic response to foods in persons with type 2 diabetes mellitus as assessed by continuous glucose monitoring system: a pilot study.

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.

Benefits of complementary therapy with insulin aspart versus human regular insulin in persons with type 2 diabetes mellitus.

BACKGROUND: Absorption rates of the phosphate-buffered insulin analogs aspart, lispro, and glulisine prevail over that of regular human insulin. The aim of this prospective observational open-label controlled study was to compare the effects of aspart and human regular insulin resulting from their sequential long-lasting routine administration in small preprandial boluses to individuals with type 2 diabetes according to identical algorithms. METHODS: Fifty-seven individuals with type 2 diabetes 64.0 +/- 1.29 (mean +/- SE) years old with diabetes' duration of 12.4 +/- 1.06 years, treated with human regular insulin for 5.2 +/- 0.44 years, and a serum C-peptide level of 1.1 +/- 0.10 nmol/L were enrolled into the study. Following two checkups performed in the course of the 364 +/- 17.9-day baseline period, human regular insulin was replaced with aspart in equivalent boluses, and two checkups in the course of 330 +/- 11.1-day sequential period were performed. The control group consisted of 17 individuals with type 2 diabetes 68.4 +/- 2.36 years old with diabetes' duration of 9.9 +/- 1.57 years, treated with insulin for 4.2 +/- 0.57 years, and a C-peptide level of 1.1 +/- 0.11 nmol/L. Data were analyzed using the statistical program SPSS version 10.1. (SPSS, Inc., Chicago, IL). RESULTS: Following the switch from human regular insulin to aspart, hemoglobin A1c (HbA1c) decreased from 8.4 +/- 0.23% at baseline to 7.9 +/- 0.17% (P = 0.031), and thereafter to 7.5 +/- 0.20% (P < 0.001), while plasma glucose concentrations in 10-point profiles, daily insulin dose (37.1 +/- 1.39 IU/day), body mass index (BMI) (30.5 +/- 0.82 kg/m(2)), and frequency of hypo- and hyperglycemic episodes did not change (P > 0.05). Patients quote satisfaction was good. No adverse events were recorded. In the control group, no significant change of baseline HbA1c (8.4 +/- 0.54%), insulin dose (33.1 +/- 3.17 IU/day), and BMI (32.1 +/- 1.12 kg/m(2)) was found. CONCLUSION: Aspart appears to be more effective than human regular insulin for complementary insulin treatment in individuals with type 2 diabetes.

Results of selfmonitoring on glucometer systems Advance and Optium in daily routine.

The aim of this prospective clinical study was to compare the results of B-glucose estimations performed simultaneously on glucometer Advance (with Micro-draw strips) and Optium (G3 strips) by lay healthy volunteers under non-standardized conditions of everyday life, to assess the difficulties dealing with lay-handling of these systems and to demonstrate the possibilities of the software Glucobalance (Hypoguard) and PC-Link (Medisense/Abbott) for the analysis of selfmonitoring. In the course of 5 days, a total of 721 pairs of measurements were carried out on 10 pairs of glucometer Advance and Optium by 10 healthy volunteers aged 16-40 years. The data transfer of all values into computer from glucometer Advance using the Glucobalance software and from glucometer Optium using the PC-Link was carried out to determine the results. The correlation of B-glucose measured on the glucometer Advance and Optium was strong (r = 0.73). Glucometer Advance brings values about 0.21 +/- 0.06 mmol/l lower than glucometer Optium. The average difference found within each pairs of glucometers Advance - Optium varied. Nevertheless, these differences are acceptable for routine selfmonitoring. The handling of glucometer Advance is not difficult for lay persons. The Glucobalance software simplifies the result evaluation by each tested person. Even though there are some advantages in comparison with the PC-Link, it should be further developed.

Determination of the glycaemic index of selected foods (white bread and cereal bars) in healthy persons.

UNLABELLED: The glycaemic index (GI) is a measure of the food power to raise blood glucose (B-glucose) concentration after a meal. For healthy eating, foods with low GI are recommended. However, for many foods in the European Union the GI has not been defined yet. The aims of this prospective open-label study were: (1) to determine the GI of white bread and juicy cereal bars FIT (Usovsko, Czech Republic) by means of the glucometer Optium (Abbott/Medisense); (2) to compare the GI of tested foods determined in the morning and in the evening hours; (3) to compare the GI of tested foods in men and women and (4) to assess the variability of the GI. METHODS: To determine the GI, measured portions of food containing 50 g of carbohydrates were eaten by 11 healthy volunteers. B-glucose curves were constructed from B-glucose values at time 0, 15, 30, 45, 60, 60, 120 min after the meal. The GI was calculated by dividing the incremental area under the curve (IAUC) for the tested food by that for the standard food (IAUCS). In each volunteer each food was tested 5 times so that 5 GI's was obtained and the average was calculated. The GI for each tested food was calculated as the mean from the respective average GI's of the 11 volunteers. MS Excel and the statistical program SPSS v. 10.1 were used to analyze the data. RESULTS: (1) The mean values of the GI for white bread was 70.3 % and for juicy cereal bars was 101.0 %, as determined in a total of 139 tests in the whole group of 11 volunteers. There was a difference when comparing white bread vs. glucose (p = 0.012) and white bread vs. cereal bars (p = 0.026) but no difference between glucose and cereal bars. (2) There was no significant difference between the GI determined in the morning and in the evening hours either for the total of 139 tests or for the individual tested foods. (3) No significant difference could be seen between the GI in men and women when comparing glucose, cereal bars and white bread. (4) There was a wide variability of GI in all tested foods: the standard deviation of GI for white bread was 30.7 %, for juicy cereal bars 38.0 %. CONCLUSIONS: The GI's for white bread and juicy cereal bars were determined. There was no difference either between the GI values determined in the morning vs. the evening hours or between the values in men vs. women. The results show wide variability. An accurate standard method for the determination of GI needs to be defined, carefully used and re-evaluated to enable a comparison of the results with various methods of other working groups.