Insulin glulisine, insulin lispro and regular human insulin show comparable end-organ metabolic effects: an exploratory study.

AIMS: To compare the end-organ metabolic effects of insulin glulisine (glulisine), insulin lispro (lispro) and regular human insulin (RHI) in patients with type 1 diabetes mellitus. METHODS: Eighteen patients with type 1 diabetes mellitus (mean age 36.9 +/- 8.6 years, BMI 23.6 +/- 2.8 kg/m(2), haemoglobin A(1c) 7.4 +/- 0.9%) were randomized in this single-centre, double-blind, three-period cross-over, standard Latin-square, euglycaemic glucose clamp trial. Patients received sequential, primed stepwise intravenous infusions of glulisine, lispro or RHI (infusion rates were increased in a stepwise manner from an initial rate of 0.33 [180 min] to 0.66 [180 min] and 1.00 [180 min] mU/kg/min). The primary variables were the suppression of endogenous glucose production (S(EGP)) and glucose uptake (GU). RESULTS: Mean basal endogenous glucose production (EGP) was 1.88, 2.12 and 2.12 mg/kg/min for glulisine, lispro and RHI respectively. Mean (+/-s.e.) maximum absolute S(EGP) (adjusted for basal EGP) was -1.64 +/- 0.06, -1.72 +/- 0.05 and -1.56 +/- 0.05 mg/kg/min respectively. Mean (+/-s.e.) maximum absolute increase in GU (adjusted for basal GU) was 6.46 +/- 0.26, 6.23 +/- 0.24 and 6.72 +/- 0.24 mg/kg/min respectively. There were no clinically relevant differences between the three insulin treatments with respect to serum insulin, free fatty acid (FFA), glycerol or lactate levels. No serious adverse events and no episodes of severe hypoglycaemia were reported. CONCLUSIONS: This study shows that glulisine, lispro and RHI have similar effects on S(EGP), GU, FFA, glycerol and lactate levels, providing evidence for similar end-organ metabolic effects.

Proportional dose-response relationship and lower within-patient variability of insulin detemir and NPH insulin in subjects with type 1 diabetes mellitus.

AIMS: This study was conducted to evaluate the dose ratio of insulin detemir and neutral protamine Hagedorn (NPH) insulin over a range of therapeutically relevant subcutaneous doses. METHODS: The study was a randomized, double-blind, crossover 24-h-iso-glycemic clamp trial in 12 C-peptide-negative type 1 diabetic patients. Each subject received, by an incomplete block design selection, two of three possible doses of insulin detemir (0.15, 0.3, 0.6 U/kg) and NPH insulin (0.15, 0.3, 0.6 IU/kg), respectively. A detailed assessment of endogenous glucose production (EGP) and glucose uptake was performed, by use of stable isotopic labeled glucose tracer (D-[6,6- (2)H (2)] glucose). RESULTS: Dose proportionality was observed within the tested dose range. Regarding unit dose ratio, 0.68 U insulin detemir equals 1 IU NPH insulin (95% CI [0.35; 1.30]). There was no statistically significant difference in effect on the area under the curve (AUC) of glucose infusion rate (GIR) (AUC (GIR)) and the maximal GIR (GIR (max)) values, when comparing U (insulin detemir) to IU (NPH insulin). The pharmacodynamic within-subject profile was lower with insulin detemir in regard to AUC (GIR 0-24 h), GIR (max) and duration of action ( P<0.05). There was a tendency for a greater reduction of EGP with insulin detemir than with NPH insulin in regard to the area over the curve (AOC) of EGP in 24 hours (AOC (EGP 0-24 h)) ( P=0.07) and minimal EPG (EGP (min)) ( P=0.02). CONCLUSIONS: These data show that insulin detemir is dose-proportional to NPH insulin in type 1 diabetic patients at clinically relevant doses. The data indicate that insulin detemir has a lower degree of within-subject variability.

Plasma and interstitial glucose dynamics after intravenous glucose injection: evaluation of the single-compartment glucose distribution assumption in the minimal models.

Recent experimental evidence suggests that estimates of glucose effectiveness (S(G)) from the minimal model of unlabeled glucose disappearance (Cold-MM) are in error. The single-compartment glucose distribution assumption embedded in the model has been indicated as a possible source of error. In this study, to directly examine the single-compartment assumption, we measured plasma and interstitial glucose concentrations after intravenous glucose injection. Additionally, we compared the accuracy of the estimates of glucose effectiveness from the Cold-MM and the single-compartment tracer minimal model (Hot-MM). Paired labeled intravenous glucose tolerance tests (IVGTTs) were performed in each of six C-peptide-negative type 1 diabetic subjects. Two different insulin infusion protocols were used: an infusion at constant basal rates and an infusion at variable rates to mimic a normal insulin response. During the labeled IVGTT with basal insulin infusion, the microperfusion technique was employed to sample adipose tissue interstitial fluid. Marked differences between the plasma and interstitial dynamics of (cold) glucose were observed during the first 22 min after glucose injection. These results suggest that the requirements for a single-compartment representation of glucose kinetics are not satisfied during at least the first 22 min of an IVGTT. Data from the labeled IVGTT with normal insulin response were used to identify the minimal-model parameters. The measure of S(G) derived using the Cold-MM was 3.44-fold higher than the direct measure obtained from the labeled IVGTT with basal insulin infusion (0.0179+/-0.0027 vs. 0.0052+/-0.0010 min(-1), P<0.01). The measure of glucose effectiveness (S(G)*) derived by the Hot-MM was 1.36-fold higher than the direct measure available from the labeled IVGTT with basal insulin infusion (0.0079+/-0.0013 vs. 0.0058+/-0.0004 min(-1), P>0.26). These results suggest that the Hot-MM is more appropriate for the evaluation of glucose effectiveness than the Cold-MM.

Simulation studies on neural predictive control of glucose using the subcutaneous route.

A novel strategy for closed-loop control of glucose using subcutaneous (s.c.) tissue glucose measurement and s.c. infusion of monomeric insulin analogues was developed and evaluated in a simulation study. The proposed control strategy is an amalgamation of a neural network and nonlinear model predictive control (NPC) technique. A radial basis function neural network was used for off-line system identification of Nonlinear Auto Regressive model with eXogenous inputs (NARX) model of the glucoregulatory system. The explicit NARX model obtained from the off-line identification procedure was then used to predict the effects of future control actions. Numerical studies were carried out using a comprehensive model of glucose regulation. The system identification procedure enabled construction of a parsimonious network from the stimulated data, and consequently, design of a controller using multiple-step-ahead predictions of the previously identified model. According to the simulation results, stable control is achievable in the presence of large noise levels and for unknown or variable physiological or technical time delays. In conclusion, the simulation results suggest that closed-loop control of glucose will be achievable using s.c. glucose measurement and s.c. insulin administration. However, the control limitations due to the s.c. insulin administration makes additional action of the patient at meal time necessary.