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

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.

Utility of different glycemic control metrics for optimizing management of diabetes

The benchmark for assessing quality of long-term glycemic control and adjustment of therapy is currently glycated hemoglobin (HbA1c). Despite its importance as an indicator for the development of diabetic complications, recent studies have revealed that this metric has some limitations; it conveys a rather complex message, which has to be taken into consideration for diabetes screening and treatment. On the basis of recent clinical trials, the relationship between HbA1c and cardiovascular outcomes in long-standing diabetes has been called into question. It becomes obvious that other surrogate and biomarkers are needed to better predict cardiovascular diabetes complications and assess efficiency of therapy. Glycated albumin, fructosamin, and 1,5-anhydroglucitol have received growing interest as alternative markers of glycemic control. In addition to measures of hyperglycemia, advanced glucose monitoring methods became available. An indispensible adjunct to HbA1c in routine diabetes care is self-monitoring of blood glucose. This monitoring method is now widely used, as it provides immediate feedback to patients on short-term changes, involving fasting, preprandial, and postprandial glucose levels. Beyond the traditional metrics, glycemic variability has been identified as a predictor of hypoglycemia, and it might also be implicated in the pathogenesis of vascular diabetes complications. Assessment of glycemic variability is thus important, but exact quantification requires frequently sampled glucose measurements. In order to optimize diabetes treatment, there is a need for both key metrics of glycemic control on a day-to-day basis and for more advanced, user-friendly monitoring methods. In addition to traditional discontinuous glucose testing, continuous glucose sensing has become a useful tool to reveal insufficient glycemic management. This new technology is particularly effective in patients with complicated diabetes and provides the opportunity to characterize glucose dynamics. Several continuous glucose monitoring (CGM) systems, which have shown usefulness in clinical practice, are presently on the market. They can broadly be divided into systems providing retrospective or real-time information on glucose patterns. The widespread clinical application of CGM is still hampered by the lack of generally accepted measures for assessment of glucose profiles and standardized reporting of glucose data. In this article, we will discuss advantages and limitations of various metrics for glycemic control as well as possibilities for evaluation of glucose data with the special focus on glycemic variability and application of CGM to improve individual diabetes management.

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.