Reduced Sample Number for Calculation of Insulin Sensitivity and Glucose Effectiveness From the Minimal Model: Suitability for Use in Population Studies

Abstract

The FSIGT has been extensively applied to the minimal model of glucose kinetics to obtain noninvasive measures of S_I. The protocol has been modified by the addition of a bolus tolbutamide or insulin injection 20 min after glucose. Although the modified protocol has improved the S, estimate, the method still requires a relatively large number of samples (n = 30). To reduce the total number of samples, we choose a sample schedule that minimizes the variance of the parameter estimates and the error in reconstructing the plasma insulin profile. With data from 10 subjects (BMI 30 ± 7 kg/m²; S_I 0.9–10.2 × 10⁻⁴ min⁻¹ · μU⁻¹ · ml⁻¹), a schedule consisting of 12 samples (0, 2, 4, 8,19, 22, 30, 40, 50, 70, 90, and 180 min) was obtained. Estimates of S_I obtained from the reduced sampling schedule were then compared with those obtained with the full sampling schedule. In all 10 individuals, the S_I estimates were almost identical. A second, much larger data base consisting of 118 modified FSIGTs performed in 87 subjects (67 men, 20 women; BMI from 19.6 to 40 kg/m² for men and 26.7 to 52.5 for women; S_I, from 0.35 to 14.1 × 10⁻⁴ min⁻¹ · μU⁻¹ · ml⁻¹) was then used to independently assess the efficacy of the reduced sampling protocol. For this data base, the correlation between S_I, which was calculated from the full versus the reduced sampling schedule, was 0.95. The mean relative deviation was –1.5% (not significantly different from zero), and the SD of the relative deviation was 20.2%. Relative deviation was defined as the percentage of difference between S_I calculated from the full sample protocol and S_I calculated from the reduced sample protocol. Thus, the reduced sampling schedule provides an unbiased estimate of a population's S_I, and an individual estimate is generally within 20% of that obtained with the full sampling schedule. A similar analysis of S_G showed that this parameter was equally well determined from the reduced compared with the full sample schedule.