PT - JOURNAL ARTICLE
AU - Steil, Garry M
AU - Murray, Joseph
AU - Bergman, Richard N
AU - Buchanan, Thomas A
TI - Repeatability of Insulin Sensitivity and Glucose Effectiveness From the Minimal Model: Implications for Study Design
DP - 1994 Nov 01
TA - Diabetes
PG - 1365--1371
VI - 43
IP - 11
4099 - http://diabetes.diabetesjournals.org/content/43/11/1365.short
4100 - http://diabetes.diabetesjournals.org/content/43/11/1365.full
SO - Diabetes1994 Nov 01; 43
AB - To determine the repeatability of insulin sensitivity measurements generated by the minimal model, we subjected 11 normal men to 3 frequently sampled intravenous glucose tolerance tests (FSIGTs) over the course of 12 days under conditions of fixed diet and limited physical activity. FSIGTs were analyzed by the minimal model using a full, 30-sample data set, as well as a reduced, 12-sample data set that has been proposed for population studies. Minimal model insulin sensitivity index (Si) calculated from the 30-sample data set averaged 0.8 ± 0.083 × 10−4 min−1 · (pmol/1)−1 (range 0.10–1.64 × 10−4 min−1 · (pmol/I)−1 with an average interday coefficient of variation (CV) of 20.2 ± 3.2% (range 6–44%). Glucose effectiveness (SG) was slightly less repeatable, with an average interday variability of 25.1 ± 8.8%. The mean CVs for first-phase insulin secretion (20.1 ± 3.5%) and total insulin secretion (21.4 ± 3.2%) were similar to the CV for Sp Mean insulin sensitivity calculated from the 12-sample data set (0.82 ± 0.08 × 10−4 min−1 · (pmol/1)−1 was not significantly different from the mean calculated from the full data set (P = 0.37, paired Student's t test). However, the mean CV of Sx calculated from the reduced data set tended to be greater than that calculated from the full data set (27.7 ± 5.4% vs. 20.2 ± 3.2%). Power calculations using the observed variances from the full and reduced data sets indicated that the full sample protocol is preferable for small studies designed to detect small changes in Si, whereas the reduced sample protocol is appropriate for studies with large numbers of subjects or large anticipated changes in Si