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.

Extended prandial glycemic profiles of foods as assessed using continuous glucose monitoring enhance the power of the 120-minute glycemic index.

BACKGROUND: The glycemic index (GI) is routinely measured 120 minutes after food intake (GI120). The purpose of this prospective open label study was to assess (1) the dynamics of glycemia over the 210 minutes following food consumption and (2) the evolution of GIs based on 120-, 150-, 180-, and 210-minute glycemic profiles. METHOD: Twenty healthy subjects (mean +/- SE; 21.9 +/- 1.39 years of age; body mass index 23.6 +/- 0.63 kg/m(2); 7 men and 13 women) completed the study. Each subject consumed 10 different foods with known GI120 on three separate occasions at four different times of day according to a defined meal plan over a 9-day period; 32 meals were evaluated. The GIs for intervals of 120, 150, 180 and 210 minutes after food consumption were determined using a continuous glucose monitoring system (CGMS) to measure glycemia. The Wilcoxon signed-rank test was applied to compare the GIs. RESULTS: Glycemia returned to baseline within 120 minutes for honey and tomato soup; within 210 minutes for white bread, choco-rice cookies, fish and potatoes, wafers, and meat ravioli with cheese; and later for dark chocolate, apricot dumplings, and choco-wheat cookies. The extended GIs were higher than the respective GI120s in eight of the foods. CONCLUSIONS: 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.

Impact of buccal glucose spray, liquid sugars and dextrose tablets on the evolution of plasma glucose concentration in healthy persons.

OBJECTIVES: The purpose of this prospective controlled trial was to assess the efficacy of three commercially available glucose products, (1) buccal glucose spray, (2) liquid sugars, and (3) dextrose tablet, on the evolution of plasma glucose concentration (PG). METHODS: Sixteen healthy volunteers aged 21.8 +/- 0.78 y (mean +/- SE), BMI 23.5 +/- 0.84 kg/m(2), tested their PG over the course of 3 sets of 4 sessions (S) each: S(0)-control fasting, S(1)-buccal administration of 10 glucose spray-doses (0.84 g of glucose) without swallowing; S(2-) consumption of 1 sachet (13 ml) of liquid sugar (ca. 5.2 g glucose, 5.2 g fructose, 5.2 g sucrose); S(3-) consumption of one dextrose tablet (6 g). PG was tested in finger-prick capillary blood using a personal glucometer Linus at the start, and at 5, 10, 15, 20 and 30 min. The means of 3 respective sessions for each of the 16 subjects were analyzed. RESULTS: The Wilcoxon signed rank test revealed no significant differences between changes in the mean PG at the start vs. 5-minute interval either in control, or any intervention sessions. Analysis of regression coefficients after 30 min compared to the control session, demonstrated an increase in PG with the sachet of liquid sugars (0.068 mmol/l/min, p = 0.001) which was greater than a single dextrose tablet (0.052 mmol/l/min, p = 0.002), but no significant PG increase was found after buccal glucose spray. CONCLUSION: Liquid sugars or dextrose tablets, but not the buccal glucose spray, are effective means to increase PG within 10 minutes after ingestion.

Benefits of three-month continuous glucose monitoring for persons with diabetes using insulin pumps and sensors.

BACKGROUND: The latest Paradigm 722 insulin pump, Medtronic MiniMed, USA, enables daily reading of 288 interstitial fluid glucose concentrations determined by a sensor inserted into subcutaneous tissue; the sensor signals are transmitted into the insulin pump, enabling the patient to see real-time glucose concentration on the display and adapt further treatment. AIMS: To assess the evolution of HbA1c over the course of a 3-month period in two cohorts of persons with type 1 (n=39) or type 2 (n=3) diabetes (PWD): 1) PWD on Paradigm 722 using sensors for continuous glucose monitoring (CGM group), 2) PWD on other types of insulin pumps performing intensive self-monitoring as before (3 to 6 times/d) on glucometer Linus, Wellion, Agamatrix (control group). METHODS: Compliant PWDs using insulin pump with insulin aspart for several previous months were included in the study. Seventeen were put on Paradigm 722 with CGM and 25 were included in the control group. Paired t-test and the statistical program SPSS v.15.0 were used to analyze the data. RESULTS: There was no significant difference in age between the two groups (P=0.996), in diabetes duration (P=0.482) or in daily insulin dose (P=0.469). In the CGM group (but not in the control group) HbA1c/IFCC dropped from 6.98+/-0.43 % to 5.98+/-0.36 % (P=0.006) within 1 month and remained reduced. CONCLUSION: The use of the Paradigm 722 insulin pump with CGM resulted in significant improvement in HbA1c which appeared within one month and remained throughout the whole 3-month study period. No significant improvement in HbA1c was seen in the control group.

Glycemic variability correlates strongly with postprandial beta-cell dysfunction in a segment of type 2 diabetic patients using oral hypoglycemic agents.

OBJECTIVE: Glucose fluctuations trigger activation of oxidative stress, a main mechanism leading to secondary diabetes complications. We evaluated the relationship between glycemic variability and beta-cell dysfunction. RESEARCH DESIGN AND METHODS: We conducted a cross-sectional study in 59 patients with type 2 diabetes (aged 64.2 +/- 8.6 years, A1C 6.5 +/- 1.0%, and BMI 29.8 +/- 3.8 kg/m(2)[mean +/- SD]) using either oral hypoglycemic agents (OHAs) (n = 34) or diet alone (nonusers). As a measure of glycemic variability, the mean amplitude of glycemic excursions (MAGE) was computed from continuous glucose monitoring data recorded over 3 consecutive days. The relationships between MAGE, beta-cell function, and clinical parameters were assessed by including postprandial beta-cell function (PBCF) and basal beta-cell function (BBCF) obtained by a model-based method from plasma C-peptide and plasma glucose during a mixed-meal test as well as homeostasis model assessment of insulin sensitivity, clinical factors, carbohydrate intake, and type of OHA. RESULTS: MAGE was nonlinearly correlated with PBCF (r = 0.54, P < 0.001) and with BBCF (r = 0.31, P = 0.025) in OHA users but failed to correlate with these parameters in nonusers (PBCF P = 0.21 and BBCF P = 0.07). The stepwise multiple regression analysis demonstrated that PBCF and OHA combination treatment were independent contributors to MAGE (R(2) = 0.50, P < 0.010), whereas insulin sensitivity, carbohydrate intake, and nonglycemic parameters failed to contribute. CONCLUSIONS: PBCF appears to be an important target to reduce glucose fluctuations in OHA-treated type 2 diabetes.

Safety of new algorithms for premeal insulin boluses in high glycaemic index meals in persons with type 1 diabetes mellitus using insulin pumps.

AIMS: Consumption of glucose or foodstuffs with high glycaemic index (GI) in persons with type 1 diabetes mellitus (PWD1) is a hot topic in present diabetology. The aim of our pilot prospective study was to assess the efficiency of empirically suggested simple algorithms for premeal boluses in PWD1 using insulin pumps and continuous glucose monitoring (CGM). METHODS: Six PWD1 (aged 46.2+/-15.09 y, diabetes duration 14.5+/-9.65 y, HbA1c/IFCC 6.3+/-1.59%, BMI 23.6+/-1.67 kg/m(2), mean+/-SD) on insulin pumps Paradigm 522/722 with RT-CGMS sensors (Medtronic MiniMed, Northridge, CA) underwent a 12-week CGM. In one week, subjects consumed 50 g of carbohydrates in eleven alternative meals (rice squares, dark chocolate, white bread, honey, glucose, ravioli with meat and Eidam cheese, mashed potatoes with fish fingers, apricot dumplings with butter, spa waffles, spalta squares, and tomato soup with pasta) eaten for breakfasts, lunches, snacks and dinners in order to calculate their GI. The insulin boluses were adjusted according to empirically defined algorithms. Average glucose levels and daily insulin doses over three one-week periods (before testing, testing and after testing) were compared. RESULTS: During the observational period, the weekly averages of glucose levels (9.1+/-2.33 mmol/l vs. 9.2+/-2.30 mmol/l vs. 9.0+/-2.43 mmol/l, respectively) and daily insulin doses (39.1+/- 8.14 IU/d vs. 39.7+/-10.7 IU/d vs. 38.6+/-9.97 IU/d, respectively) were similar. One-week consumption of high GI foodstuffs had only a negligeable effect on average glucose levels. CONCLUSION: The suggested algorithms for premeal insulin boluses appear to limit the risk of potential hyperglycaemia resulting from intake of high GI foodstuffs.

Chronic hyperglycemia but not glucose variability determines HbA1c levels in well-controlled patients with type 2 diabetes.

To determine the relationships between HbA1c, characteristics of hyperglycemia and glycemic variability in well-controlled type 2 diabetes (HbA1c<7.0%), we studied 63 primary-care patients (36 men and 27 women), aged 34-75 years, with type 2 diabetes for 2-32 years using a continuous glucose monitoring system (CGMS) and standardized meal test (MMT). Duration of hyperglycemia (>8.0 mmol/l), standard deviation score (S.D.-score) and mean amplitude of glycemic excursions (MAGE) were analyzed from CGMS data and postprandial glucose during MMT (PPG(MMT)). Patients were hyperglycemic for 5.7h/day (median), experienced 4.1 hyperglycemic episodes/day, and 78% exceeded PPG levels of 8.0 mmol/l. HbA1c, though associated with the extent of hyperglycemia (r=0.40, p<0.001), failed to correlate with S.D.-score and MAGE. Multiple regression analysis demonstrated that HbA1c was predicted only by fasting glucose (R(2)=0.24, p<0.001) but neither by PPG(MMT), duration of hyperglycemia, S.D.-score nor MAGE. CGMS and meal test provide the tools for complete characterization of glycemia in type 2 diabetes. In well-controlled type 2 diabetes, HbA1c correlates with chronic hyperglycemia but not with glucose variability. Our data suggest that chronic sustained hyperglycemia and glucose fluctuations are two independent components of dysglycemia in diabetes.