Computer Simulation Model to Train Medical Personnel on Glucose Clamp Procedures

OBJECTIVE

A glucose clamp procedure is the most reliable way to quantify insulin pharmacokinetics and pharmacodynamics, but skilled and trained research personnel are required to frequently adjust the glucose infusion rate. A computer environment that simulates glucose clamp experiments can be used for efficient personnel training and development and testing of algorithms for automated glucose clamps.

METHODS

We built 17 virtual healthy subjects (mean age, 25±6 years; mean body mass index, 22.2±3 kg/m²), each comprising a mathematical model of glucose regulation and a unique set of parameters. Each virtual subject simulates plasma glucose and insulin concentrations in response to intravenous insulin and glucose infusions. Each virtual subject provides a unique response, and its parameters were estimated from combined intravenous glucose tolerance test-hyperinsulinemic-euglycemic clamp data using the Bayesian approach. The virtual subjects were validated by comparing their simulated predictions against data from 12 healthy individuals who underwent a hyperglycemic glucose clamp procedure.

RESULTS

Plasma glucose and insulin concentrations were predicted by the virtual subjects in response to glucose infusions determined by a trained research staff performing a simulated hyperglycemic clamp experiment. The total amount of glucose infusion was indifferent between the simulated and the real subjects (85±18 g vs. 83±23 g; p=NS) as well as plasma insulin levels (63±20 mU/L vs. 58±16 mU/L; p=NS).

CONCLUSIONS

The virtual subjects can reliably predict glucose needs and plasma insulin profiles during hyperglycemic glucose clamp conditions. These virtual subjects can be used to train personnel to make glucose infusion adjustments during clamp experiments.

The StatStrip glucose monitor is suitable for use during hyperinsulinemic euglycemic clamps in a pediatric population

BACKGROUND

The hyperinsulinemic euglycemic clamp is the gold standard for assessment of insulin resistance and requires frequent, accurate measurements of blood glucose concentrations, typically utilizing the YSI 2300 STAT Plus™ glucose analyzer (YSI, Inc., Yellow Springs, OH). Despite its accuracy, the YSI has several limitations, including its cost, lengthy run time, need for trained personnel, frequent maintenance, and large blood volumes. Simpler hospital-grade hand-held glucose meters are now available but have not been validated for use in pediatric clamp settings. Our objective was to evaluate the accuracy, precision, and reliability of the StatStrip(®) (SS) hospital glucose monitoring system (Nova Biomedical, Waltham, MA) relative to the YSI 2300 STAT glucose analyzer in pediatric hyperinsulinemic euglycemic clamps.

SUBJECTS AND METHODS

Four hundred sixty blood specimens drawn from 11 pediatric patients undergoing hyperinsulinemic euglycemic clamps were simultaneously analyzed by SS and YSI. Outcome measures included SS bias relative to YSI and glucose measurement precision on SS and YSI.

RESULTS

The SS showed a slight positive bias of 0.75 ± 2.83 mg/dL versus the YSI. Percentage coefficients of variance for SS and YSI were 9.53% and 9.25%, respectively. Using a Bland-Altman plot, the limits of agreement were ± 5.7 mg/dL. The coefficient of repeatability for SS was 6.63; the coefficient of individual agreement between the YSI and SS was 0.995.

CONCLUSIONS

The SS is a suitable replacement for the YSI in pediatric hyperinsulinemic euglycemic clamp studies, is easier to use, more cost-effective, and faster, and requires less blood. Future euglycemic clamp studies can consider utilizing this methodology.

Artificial neural networks based controller for glucose monitoring during clamp test

Insulin resistance (IR) is one of the most widespread health problems in modern times. The gold standard for quantification of IR is the hyperinsulinemic-euglycemic glucose clamp technique. During the test, a regulated glucose infusion is delivered intravenously to maintain a constant blood glucose concentration. Current control algorithms for regulating this glucose infusion are based on feedback control. These models require frequent sampling of blood, and can only partly capture the complexity associated with regulation of glucose. Here we present an improved clamp control algorithm which is motivated by the stochastic nature of glucose kinetics, while using the minimal need in blood samples required for evaluation of IR. A glucose pump control algorithm, based on artificial neural networks model was developed. The system was trained with a data base collected from 62 rat model experiments, using a back-propagation Levenberg-Marquardt optimization. Genetic algorithm was used to optimize network topology and learning features. The predictive value of the proposed algorithm during the temporal period of interest was significantly improved relative to a feedback control applied at an equivalent low sampling interval. Robustness to noise analysis demonstrates the applicability of the algorithm in realistic situations.

Evaluation of a novel continuous glucose measurement device in patients with diabetes mellitus across the glycemic range

BACKGROUND

This glucose clamp study assessed the performance of an electrochemical continuous glucose monitoring (CGM) system for monitoring levels of interstitial glucose. This novel system does not require use of a trocar or needle for sensor insertion.

METHOD

Continuous glucose monitoring sensors were inserted subcutaneously into the abdominal tissue of 14 adults with type 1 or type 2 diabetes. Subjects underwent an automated glucose clamp procedure with four consecutive post-steady-state glucose plateau periods (40 min each): (a) hypoglycemic (50 mg/dl), (b) hyperglycemic (250 mg/dl), (c) second hypoglycemic (50 mg/dl), and (d) euglycemic (90 mg/dl). Plasma glucose results obtained with YSI glucose analyzers were used for sensor calibration. Accuracy was assessed retrospectively for plateau periods and transition states, when glucose levels were changing rapidly (approximately 2 mg/dl/min).

RESULTS

Mean absolute percent difference (APD) was lowest during hypoglycemic plateaus (11.68%, 14.15%) and the euglycemic-to-hypoglycemic transition (14.21%). Mean APD during the hyperglycemic plateau was 17.11%; mean APDs were 18.12% and 19.25% during the hypoglycemic-to-hyperglycemic and hyperglycemic-to-hypoglycemic transitions, respectively. Parkes (consensus) error grid analysis (EGA) and rate EGA of the plateaus and transition periods, respectively, yielded 86.8% and 68.6% accurate results (zone A) and 12.1% and 20.0% benign errors (zone B). Continuous EGA yielded 88.5%, 75.4%, and 79.3% accurate results and 8.3%, 14.3%, and 2.4% benign errors for the euglycemic, hyperglycemic, and hypoglycemic transition periods, respectively. Adverse events were mild and unlikely to be device related.

CONCLUSION

This novel CGM system was safe and accurate across the clinically relevant glucose range.

Glucose clamp algorithms and insulin time-action profiles

MOTIVATION

Most current insulin pumps include an insulin-on-board (IOB) feature to help subjects avoid problems associated with "insulin stacking." In addition, many control algorithms proposed for a closed-loop artificial pancreas make use of IOB to reduce the probability of hypoglycemic events that often occur due to the integral action of the controller. The IOB curves are generated from the pharmacodynamic (time-activity profiles) actions of subcutaneous insulin, which are obtained from glycemic clamp studies.

METHODS

Glycemic clamp algorithms are reviewed and in silico studies are performed to analyze the effect of glucose meter bias and noise on glycemic control and the manipulated glucose infusion rates. The glucose infusion rates are used to obtain insulin time-activity profiles, which are then used to generate IOB curves.

RESULTS

A model-based, three-step-ahead controller is shown to be equivalent to a proportional-integral control algorithm with time-delay compensation. A systematic glucose meter bias of +6 mg/dl results in a decrease in the glucose area under the curve of 3% but no change in the IOB profiles.

CONCLUSIONS

Based on these preliminary simulation studies, a substantial amount of glucose meter bias and noise during a glycemic clamp can be tolerated with little net effect on the IOB curves. It is suggested that handheld glucose meters can therefore be used in clamp studies if the measurements are filtered (averaged) before processing by the control algorithm. Clinical studies are needed to confirm these preliminary results.

Chromium picolinate for insulin resistance in subjects with HIV disease: a pilot study

AIM

Multidrug regimens in HIV disease are associated with an increased incidence of insulin resistance, by as much as 50%. Not only does insulin resistance predisposes subjects to diabetes but also it is associated with the metabolic syndrome and increased risk of cardiovascular disease. Previous studies suggest that chromium picolinate can improve insulin resistance in patients with type 2 diabetes. The objective was to study the efficacy and safety of chromium picolinate as a treatment of insulin resistance in subjects infected with HIV.

METHODS

The ability of chromium picolinate (1000 mug/day) to improve insulin sensitivity, determined with a hyperinsulinaemic-euglycaemic insulin clamp, was determined in eight HIV-positive subjects on highly active antiretroviral therapy.

RESULTS

The mean rate of glucose disposal during the clamp was 4.41 mg glucose/kg lean body mass (LBM)/min (range 2.67-5.50), which increased to 6.51 mg/kg LBM/min (range 3.19-12.78, p = .03), an increase of 25% after 8 weeks of treatment with chromium picolinate. There were no significant changes in blood parameters, HIV viral burden or CD4+ lymphocytes with chromium picolinate treatment. Two subjects experienced abnormalities of liver function during the study. Another subject experienced an elevation in blood urea nitrogen.

CONCLUSIONS

The study shows that chromium picolinate therapy improves insulin resistance in some HIV-positive subjects, but with some concerns about safety in this population.

Interleukin-6 and tumor necrosis factor-alpha are not increased in patients with Type 2 diabetes: evidence that plasma interleukin-6 is related to fat mass and not insulin responsiveness

AIMS/HYPOTHESIS

Our aim was to examine the possible direct relationship of interleukin-6 and TNFalpha with insulin sensitivity in humans.

METHODS

We carried out two series of euglycaemic-hyperinsulinaemic clamp experiments. In the first (CLAMP1), skeletal muscle mRNA expression and plasma concentrations of IL-6 and TNFalpha were examined in patients with Type 2 diabetes ( n=6), subjects matched for age (n=6), and young healthy (n=11) control subjects during a 120-min supra-physiological hyperinsulinaemic (40 mU.m(-2).min(-1)) euglycaemic clamp. In the second series of experiments (CLAMP2), patients with Type 2 diabetes (n=6) and subjects matched for age (n=7) were studied during a 240-min high-physiological hyperinsulinaemic (7 mU.m(-2).min(-1)) euglycaemic clamp, during which arterial and venous (femoral and subclavian) blood samples were measured for IL-6 and TNFalpha flux.

RESULTS

In both experiments the glucose infusion rate in the patients was markedly lower than that in the other groups. In CLAMP1, basal skeletal muscle IL-6 and TNFalpha mRNA were the same in all groups. They were not affected by insulin and they were not related to the glucose infusion rate. In CLAMP2, neither cytokine was released from the arm or leg during insulin stimulation in either group. In both experiments plasma concentrations of these cytokines were similar in the patients and in the control subjects, although in CLAMP1 the young healthy control group had lower (p<0.05) plasma IL-6 concentrations. Using data from all subjects, a strong positive correlation (r=0.85; p<0.00001) was observed between basal plasma IL-6 and BMI. Conversely, a negative relationship (r=-0.345; p<0.05) was found between basal plasma TNFalpha and BMI, although this was not significant when corrected for BMI. When corrected for BMI, no relationship was observed between either basal plasma IL-6 or TNFalpha and GIR.

CONCLUSIONS/INTERPRETATION

These data show that the increased circulating IL-6 concentrations seen in patients with Type 2 diabetes are strongly related to fat mass and not insulin responsiveness, and suggest that neither IL-6 nor TNFalpha are indicative of insulin resistance.

[Assessment of insulin sensitivity during exercise training program in obese women. Comparison of simple indices with hyperinsulinemic euglycemic clamp technique]

Insulin resistance is a key element of metabolic syndrome, which includes disturbances of glucose tolerance, obesity, hypertension, coronary heart disease dyslipidemia and many other defects. An important problem in scientific research is precise measurement of insulin sensitivity. The method considered "the gold standard" is glucose clamp, however, it is difficult to apply this method in large studies. Therefore, simple indices of insulin resistance are proposed. It remains unclear whether those indices are able to reflect changes occurring during insulin-sensitizing intervention. The aim of the present study was to assess the use of indirect indices for the changes in insulin sensitivity during exercise training and to compare those indices with results derived from clamp. Fourteen obese normoglycemic women participated in 12-week exercise training program, which included exercise performed on a bicycle ergometer, 5 days a week for 30 minutes. Insulin sensitivity (M/FFM value) before and after training was measured with hyperinsulinemic euglycemic clamp technique. Simple indices of insulin resistance were also assessed: fasting plasma insulin (INS), logarithm INS (log [INS]), homeostasis model assessment (HOMA), logarithm HOMA (log [HOMA]) and quantitative insulin sensitivity check index (QUICKI). Before training, all those indices were markedly related to M/FFM. After training, an increase in M/FFM was observed. None of the examined indices markedly changed after training. There was no correlations between changes of evaluated indices and in M/FFM during training, and no relationships of those parameters after training. Our study indicates that simple indices are not able to reflect changes occurring during insulin-sensitizing intervention.

[Insulin resistance in obese subjects with impaired glucose tolerance. Studies with hyperinsulinemic euglycemic clamp technique]

Insulin resistance is a key factor in the pathogenesis of impaired glucose tolerance (IGT) and type 2 diabetes and is also associated with greater risk for cardiovascular disease. Insulin resistance is more common in obese individuals and is considered to be the link between obesity and IGT and diabetes. The aim of the present study was to assess insulin resistance in obese subjects with IGT. We examined 57 subjects with marked overweight or obesity (BMI > > 27.8 kg x m-2), 27 with IGT and 30 with normal glucose tolerance (NGT), assessed by an oral glucose tolerance test, according to WHO criteria. Thirty lean (BMI < 25 kg x m-2) healthy subjects served as a control group. Anthropometric and biochemical parameters were measured. Insulin sensitivity was evaluated with hyperinsulinemic euglycemic clamp technique. Subjects with IGT had higher levels of glucose, insulin, non-esterified fatty acids and glycated hemoglobin than obese with NGT, all those parameters were also higher in both obese groups in comparison to controls. We showed significant differences in insulin sensitivity between the studied groups, an index of the whole-body glucose uptake was decreased in both obese groups in comparison to controls, and it was also lower in IGT than in obese NGT group. We observed marked negative correlations between insulin sensitivity and estimated anthropometric and biochemical parameters. Our study indicates that insulin resistance is an important factor determining a deterioration of glucose tolerance in subjects with overweight and obesity.