EFFECT OF HEPARIN ON INSULIN-GLUCOSE INTERACTIONS MEASURED BY THE MINIMAL MODEL TECHNIQUE - IMPLICATIONS FOR REPRODUCTIBILITY USING THIS METHOD

The minimal model technique permits investigation of glucose and insulin interactions during a frequently sampled intravenous glucose tolerance test (FSIGT). The model allows measurement of several important variables including insulin sensitivity (SI), glucose effectiveness at basal insulin (SG), and glucose effectiveness at zero insulin (GEZI). In addition, from the FSIGT, first-phase insulin secretion (AIRglucose) and the glucose disappearance constant (Kg) can be estimated. The estimates obtained using the minimal model technique could be of importance in understanding potential relationships between carbohydrate and lipid metabolism. In studying lipoprotein lipase (LPL) activity and mass as one of the elements of lipid metabolism, heparin administration is necessary. However, the effect of administration of this agent on factors important in carbohydrate metabolism has not been fully elucidated. Therefore, to assess the effect of heparin on insulin-glucose interactions, we performed paired studies in which subjects randomly underwent FSIGT studies 20 minutes following bolus injections of heparin or saline. None of the measured parameters was influenced by heparin administration just before the FSIGT. Since these estimates were not affected by heparin administration, these studies also permitted assessment of the coefficient of variation of replicate analysis for all values generated using the minimal model technique. The coefficients of variation of replicate analysis calculated from these two studies were 16.9% for SI, 16.6% for SG, 18.3% for GEZI, 20.6% for AIRglucose, and 14.5% for Kg. These results suggest that heparin can be administered as part of a procedure that would allow concurrent assessment of various aspects of both carbohydrate and lipid metabolism. The measured variability of the different measures appears to result from biologic and laboratory factors. These coefficients of variation of replicate analysis should be considered when evaluating whether individual changes measured using the minimal model are real or might be accounted for by the variability of the experimental method. © 1993.