Continuous Glucose Monitoring - A Novel Approach to the Determination of the Glycaemic Index of Foods (DEGIF 1)

Apple preload increased postprandial insulin sensitivity of a high glycemic rice meal only at breakfast

PURPOSE

The possible impact of preload food on insulin sensitivity has yet been reported. This study aimed to investigate the glycemic and insulinemic effect of an apple preload before breakfast, lunch and early supper, based on high glycemic index (GI) rice meals.

METHODS

Twenty-three healthy participants in Group 1 and 14 participants in Group 2 were served with the reference meal (white rice containing 50 g of available carbohydrate) or experimental meals (apple preload and rice, each containing 15 and 35 g of available carbohydrate). The meals were either served at 8:00 for breakfast, 12:30 for lunch or 17:00 for early supper to explore the possible effect of time factor. The group 1 assessed the postprandial and subsequent-meal glycemic effect of the test meals by continuous glucose monitoring (CGM), along with subjective appetite; The group 2 further investigated the glycemic and insulin effect by blood collection.

RESULTS

The apple preload lowered the blood glucose peak value by 33.5%, 31.4% and 31.0% in breakfast, lunch and supper, respectively, while increased insulin sensitivity by 40.5% only at breakfast, compared with the rice reference. The early supper resulted significantly milder glycemic response than its breakfast and lunch counterparts did. The result of CGM tests was consistent with that of the fingertip blood tests.

CONCLUSION

Apple preload performed the best at breakfast in terms of enhancing the insulin sensitivity. The preload treatment could effectively attenuate postprandial GR without increasing the area under insulin response curve in any of the three meals.

Raised FGF-21 and Triglycerides Accompany Increased Energy Intake Driven by Protein Leverage in Lean, Healthy Individuals: A Randomised Trial

A dominant appetite for protein drives increased energy intake in humans when the proportion of protein in the diet is reduced down to approximately 10% of total energy. Compensatory feeding for protein is apparent over a 1–2 d period but the mechanisms driving this regulation are not fully understood. Fibroblast growth factor-21 (FGF-21) has been identified as a candidate protein signal as levels increase in the circulation when dietary protein is low. The aim of this randomised controlled trial was to assess whether changes in percent dietary protein over a 4 d ad libitum experimental period in lean, healthy participants influenced energy intake, metabolic health, circulating FGF-21 and appetite regulating hormones including ghrelin, glucagon like peptide-1 and cholecystokinin. Twenty-two lean, healthy participants were fed ad libitum diets containing 10, 15 and 25% protein, over three, 4 d controlled, in-house experimental periods. Reduced dietary protein intake from 25% to 10% over a period of 4 d was associated with 14% increased energy intake (p = 0.02) as previously reported, and a 6-fold increase in fasting circulating plasma FGF-21 levels (p<0.0001), a 1.5-fold increase in serum triglycerides (p<0.0001), and a 0.9-fold decrease in serum total cholesterol (p = 0.02). Serum HDL cholesterol was reduced with a reduction in dietary protein from 15% to 10% (p = 0.01) over 4 d but not from 25% to 10% (p = 0.1) and the change from baseline was not different between diets. Plasma fasting insulin levels following the 4 d study period were significantly lower following the 25% ad libitum study period compared to the 15% protein period (p = 0.014) but not the 10% protein period (p = 0.2). Variability in interstitial glucose during each study period increased with a decrease in dietary protein from 25% to 15% and 10% (p = 0.001 and p = 0.04, respectively). Ghrelin, glucagon-like peptide-1 and cholecystokinin were unchanged. Increases in energy intake, plasma FGF-21 and serum triglycerides were associated with reductions in percent dietary protein from 25% to 10% energy over a 4 d ad libitum in-house feeding period and may be important in regulation of dietary protein intake.

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.

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.

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.

No difference in the 24-hour interstitial fluid glucose profile with modulations to the glycemic index of the diet

OBJECTIVE

Reducing the glycemic index (GI) of the diet may decrease metabolic risk, primarily through reduction and stabilization of blood glucose. The objective of this research was to investigate whether incorporation of lower or higher GI foods into mixed meals had different effects on daylong glucose profiles, measured in interstitial fluid by a continuous glucose-monitoring system.

METHODS

The study was a randomized, balanced, two-way crossover intervention of 2 x 1-wk periods of lower and higher GI diets. Participants were 12 overweight healthy adult women (mean body mass index +/- standard deviation 27.5+/-2.3 kg/m(2)). Changes in GI were achieved through substitution of key staple carbohydrate-rich foods. After a 4-d run-in on each dietary regimen, participants wore the continuous glucose-monitoring system over 2 d of identical controlled feeding in the laboratory, separated by 1 d of ad libitum consumption at home.

RESULTS

On controlled days, diets differed in GI by 15 U and provided equal energy, macronutrients, and fiber. On ad libitum days, diet diaries revealed a difference in GI of 14+/-1 U (mean +/- standard error), with no detectable difference in energy, macronutrient, or fiber intake. No differences were observed in glucose profiles between higher and lower GI interventions in the controlled or ad libitum setting. There was significant agreement in area under the glucose curve on repeated controlled feeding days (intraclass correlation 0.75).

CONCLUSION

This study indicates that a difference in dietary GI of 14-15 U is insufficient to alter daylong glycemia as measured in interstitial fluid by the continuous glucose-monitoring system.

Variability of the glycemic response to single food products in healthy subjects

BACKGROUND

Many studies on the health effects of the glycemic index (GI) are confounded by differences in the intakes of other macronutrients and fibre. Little data exist about the within- and between-subject variability of the GI.

OBJECTIVE

Our objectives were therefore (i) to calculate the GI of eight commonly used food products with similar macronutrient and fibre composition, but with different sources of carbohydrates, (ii) to examine the inter- and intra-individual variability of the incremental area under the curve (iAUC) after consuming the reference solution, and (iii) to compare the effect of three different methods on 2-h postprandial blood glucose responses.

DESIGN

Four groups of 10 healthy subjects consumed in random order the increased (iGI) and decreased GI (dGI) variants and twice a glucose solution. All products consisted of 25g available carbohydrates (CHO). For the fruit drink, glucose values were simultaneously analyzed using venous and capillary blood samples, and by using a continuous glucose monitoring system (CGMS).

RESULTS

The GIs for increased and decreased variants were (mean+/-standard error of the mean (SEM)) 69+/-15 and 40+/-4 for bread, 86+/-14 and 48+/-8 for a fruit drink, 51+/-12 and 20+/-4 for cake, and 63+/-17 and 37+/-10 for a cookie. The inter- and intra-individual coefficient of variation (CV) of the iAUCs of the reference solution was large and varied respectively between 13 and 38%, and between 33 and 80%.

CONCLUSIONS

These data suggest that the GI is difficult to use at the individual level.

Evaluation of the new software program DegifXL4 in the determination of the glycaemic indices of foodstuffs

AIMS

There is no standardized protocol for measuring glycemic index (GI) that takes time-of-day effects into account. The software DegifXL2 and Medtronic-Minimed's CGMS and Solutions, makes the GI calculation at breakfast and dinner time possible. The aim of this study was to assess the enhanced data processing software (DegifXL4) enabling the GI calculation at breakfast, lunch, afternoon snack and dinner times.

METHODS

The glucose levels of 20 healthy volunteers were monitored after they consumed either 50 g of glucose or one of ten alternative foodstuffs either for breakfast and dinner or for lunch or snack. Within the 9-day test period, 10 such meals were monitored in 3 replicates for each volunteer. Specifically, CGMS was used to monitor plasma glucose levels at 5-minute intervals for a period of 120 min following the foodstuff ingestion.

RESULTS

Using the enhanced spreadsheed DegifXL 4, a total of 640 profiles were obtained and 491 (77 %) accomplished the criteria for further processing. The percentage of successful tests in each foodstuff varied from 57 to 87 %.

CONCLUSIONS

The use of the new software DegifXL4 offers accurate GI estimates for foodstuffs eaten for breakfast, lunch, snacks and dinners in three replicates. In combination with the CGMS Solutions Software is DegifXL4 an enhanced efficient and comfortable way to routinely measure GI values.

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.

Occurence of adverse events due to continuous glucose monitoring

AIMS

Continuous glucose monitoring (CGM) using transcutaneous sensors is becoming a sophisticated method to control and regulate glucose metabolism. The transcutaneous sensor of the CGM system (CGMS Medtronic Minimed, Northridge, CA, USA) is chosen to measure glucose concentration in interstitial fluid up to three days after insertion even though its function remains stable for a longer period. The question arises, which factors really limit the period of sensor insertion without unnecessary risk. The aim of this study was to assess any adverse events occurring in the course of 9 days after the sensor insertion.

METHODS

In a group of 22 healthy volunteers aged 21.8+/-1.30 y (mean +/- SE) a total of 26 sensors was inserted subcutaneously in gluteal or lumbar region for 9 days. Before insertion the site was sprayed with an antiseptic (Cutasept F, Bode Chemie, Hamburg, Germany). Local adverse reactions and disturbances in general condition were examined.

RESULTS

In the course of 184 sensor-days, there were only minor local adverse events: hypersensitivity, itching, pain, redness, burning, subcutaneous hemorrhage. Additionally, sleep disturbances, attention deficits, problems related to the CGMS monitor, to adhesive tape and/or sensor were found. None of these resulted in sensor withdrawal. In 12 volunteers (55 %) no complications were observed. The sensor function measured according to electrical signals (ISIG) failed (always on day 1-2) in 4 cases (16 %).

CONCLUSIONS

The present FDA approved 3-day insertion period for Medtronic transcutaneous sensor does not seem to limit its use and appears to be worth a careful revision.

Glycaemic index of selected foodstuffs in healthy persons

AIMS

The aim of this study was to determine glycaemic index (GI) of 10 popular foodstuffs/mixed meals in healthy persons.

METHODS

Ten tested foodstuffs and glucose standard were consumed in three replicates in the course of a defined 9-day meal plan: puffed rice squares with chocolate, dark chocolate, white bread, honey and glucose for breakfast (at 7 a.m.) and dinner (at 8 p.m.); pasta with meat, fried fish with mashed potatoes, and buttered apricot dumplings for lunch (at 12 a.m.); wafers, puffed spelt squares with chocolate, and tomato soup for snack (at 4 p.m.). Each portion contained 50 g of carbohydrates and was consumed within 30 minutes. Glucose concentrations were measured by means of the Continous Glucose Monitoring System (CGMS, Medtronic Minimed, Northridge, CA, USA). The results were processed by Solutions Software (Medtronic Minimed, Northridge, CA, USA) and DegifXL4 software, Palacký University, Olomouc, CZ. Twenty healthy persons aged 21.9 +/- 1.39 y (mean +/- SE), BMI 23.6 +/- 0.63 kg/m(2) completed the study.

RESULTS

GI of tested foodstuffs ranged from 34.7 % (chocolate) to 105.3 % (puffed rice squares with chocolate). There were more than tenfold differences between minimal and maximal values of the GI for some foodstuffs. Significant interindividual differences were found between GIs of foodstuffs.

CONCLUSIONS

In twenty healthy persons the glycaemic indexes of ten popular foodstuffs were determined, to be added to the nutritional labels in order to facilitate the optimum meal planning.

Automated computation of glycemic index for foodstuffs using continuous glucose monitoring

BACKGROUND

The glycemic index (GI) is a measure of the ability of a food to raise glucose levels after it is eaten. Continuous glucose monitoring (CGM) has been shown to give identical values of GI when compared to traditional methods. However, there has been no standardized protocol for measuring GI that takes into account interindividual variability and chronophysiological glycemic response to food. Our aim was (1) to create and describe software based on a Microsoft Excel 2000 spreadsheet to facilitate rapid, automated, accurate, and standardized processing of data obtained using recent CGM methodology to measure GI and its variability and (2) to assess the benefits of this new approach.

METHOD

Twenty healthy subjects consumed 50 grams of glucose or four alternative foodstuffs (chocolate, apple baby food, rice squares, or yogurt) at breakfast and dinner during 1 week, resulting in 300 CGMS glucose profiles; 92% of meal tests were satisfactory for evaluation. Application and functions of the software DegifXL are described.

RESULTS

Using the new spreadsheet software DegifXL, time required for data processing for the 15 data sets for each subject was reduced from 2000 to 160 minutes relative to previously used manual methods. We characterized the GI for four foodstuffs with three replicate measurements in each of 20 subjects and evaluated between person, between time period, and between replicate GI variabilities.

CONCLUSION

DegifXL, combined with CGM, was an efficient and effective tool for routine measurement of group- and subject-related GI.

Continuous glucose profiles in healthy subjects under everyday life conditions and after different meals

BACKGROUND

This study investigated continuous glucose profiles in nondiabetic subjects.

METHODS

Continuous interstitial glucose measurement was performed under everyday life conditions (2 days) and after ingestion of four meals with standardized carbohydrate content (50 grams), but with different types of carbohydrates and variable protein and fat content. Twenty-four healthy volunteers (12 female, 12 male, age 27.1 +/- 3.6 years) participated in the study. Each subject wore two microdialysis devices (SCGM1, Roche Diagnostics) simultaneously.

RESULTS

The mean 24-hour interstitial glucose concentration under everyday life conditions was 89.3 +/- 6.2 mg/dl (mean +/- SD, n = 21), and mean interstitial glucose concentrations at daytime and during the night were 93.0 +/- 7.0 and 81.8 +/- 6.3 mg/dl, respectively. The highest postprandial glucose concentrations were observed after breakfast: 132.3 +/- 16.7 mg/dl (range 101-168 mg/dl); peak concentrations after lunch and dinner were 118.2 +/- 13.4 and 123.0 +/- 16.9 mg/dl, respectively. Mean time to peak glucose concentration was between 46 and 50 minutes. After ingestion of standardized meals with fast absorption characteristics, peak interstitial glucose concentrations were 133.2 +/- 14.4 and 137.2 +/- 21.1 mg/dl, respectively. Meals with a higher fiber, protein, and fat content induced a smaller increase and a slower decrease of postprandial glucose concentrations with peak values of 99.2 +/- 10.5 and 122.1 +/- 20.4 mg/dl, respectively.

CONCLUSIONS

This study provided continuous glucose profiles in nondiabetic subjects and demonstrated that differences in meal composition are reflected in postprandial interstitial glucose concentrations. Regarding the increasing application of continuous glucose monitoring in diabetic patients, these data suggest that detailed information about the ingested meals is important for adequate interpretation of postprandial glucose profiles.

Function and accuracy of glucose sensors beyond their stated expiry date

BACKGROUND

The sensor of the Continuous Glucose Monitoring System (CGMS, Medtronic Minimed, Northridge, CA) is labeled to expire 6 months following its production and to measure the glucose concentration in interstitial fluid up to 3 days after insertion. The purpose of this study was to demonstrate potential possibilities of sensors when used beyond their expiry date.

METHODS

Twenty sensors, each between 3 to 18 months after the expiry date, were assessed in a 7-day period after insertion. Twenty healthy volunteers 23.4 +/- 2.92 (mean +/- SD) years old were trained in handling the CGMS and the Hypoguard (Woodbridge, UK) Advance glucometer system to measure their capillary plasma glucose concentration 18 times a day. Sensor function was estimated according to the number of readings per day, the accuracy according to the mean absolute difference (MAD), and correlation coefficient (r) between glucometer and sensor resulting from paired values.

RESULTS

Uninterrupted sensor function was found in 117 of 140 sensor-days (83.6%). A reduction of readings in 23 sensor-days (16.4%) was caused by user error (5 sensor-days, 3.6%), connecting cable (7 sensor-days, 5%), sensor failure (8 sensor-days, 5.7%), or uncertain factors (3 sensor-days, 2.1%). MAD was always < 28%, and r = 0.79.

CONCLUSIONS

Neither the expiry date nor the 3-day period of use limits the reliable function of a CGMS sensor. Sensors were found to function as long as 18 months after the expiry date, mostly for at least 7 days. There were no serious local adverse reactions. Prolongation of shelflife label and insertion time appears to be reasonable. Further studies are in progress.