Reassessment of Glucose Effectiveness and Insulin Sensitivity From Minimal Model Analysis: A Theoretical Evaluation of the Single-Compartment Glucose Distribution Assumption

Minimal model analysis with the frequently sampled intravenous glucose tolerance test provides an effective way to measure two important metabolic parameters in vivo under non-steady-state conditions: glucose effectiveness (S_G) and insulin sensitivity (S_I). Two questions regarding the validity of S_G and S_I have recently emerged. First, S_G from the minimal model is suspected to be overestimated. Second, the occurrence of S_I values indistinguishable from zero (“zero-S_I”) is not negligible in large clinical studies, and its physiological meaning is uncertain. In this study, we examined the significance of the assumed single-compartment glucose distribution embedded in the minimal model on the estimation of S_G and S_I. A more accurate two-compartment model was constructed by incorporating insulin action on hepatic glucose output and uptake into a previously validated construction. The two-compartment results were compared with the one-compartment minimal model results. It was shown that the one-compartment assumption contributes to a systematic deviation of S_G (slope = 0.54, y-intercept = 0.014 min⁻¹; n = 195 simulations). However, S_G from the minimal model was linearly correlated to S_G determined from the two-compartment model (r = 0.996). The one-compartment assumption also contributed to the occurrence of zero S₁ values for insulin-resistant subjects. A similar linear relationship was found between S₁ estimated by both the minimal model and the two-compartment model (slope = 0.58, y-intercept = −0.57 × 10⁻⁴ min⁻¹ per μU/ml, r = 0.998). In conclusion, S_G and S_I from the minimal model are not necessarily equivalent to values emanating from the more accurate two-compartment model. However, the very high correlation between one- and two-compartment results suggests that the minimal model-derived S_G and S_I are dependable indexes of in vivo glucose effectiveness and insulin sensitivity. Minimal model analysis' advantages of simplicity, minimal invasiveness, reasonable reflection of non-steady-state glucose kinetics, and cost-effectiveness could in many cases outweigh the structural bias introduced by the model simplification.