The FSIGT has been extensively applied to the minimal model of glucose kinetics to obtain noninvasive measures of SI. 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; SI 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 SI obtained from the reduced sampling schedule were then compared with those obtained with the full sampling schedule. In all 10 individuals, the SI 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; SI, 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 SI, 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 SI calculated from the full sample protocol and SI calculated from the reduced sample protocol. Thus, the reduced sampling schedule provides an unbiased estimate of a population's SI, and an individual estimate is generally within 20% of that obtained with the full sampling schedule. A similar analysis of SG showed that this parameter was equally well determined from the reduced compared with the full sample schedule.
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Original Articles|
February 01 1993
Reduced Sample Number for Calculation of Insulin Sensitivity and Glucose Effectiveness From the Minimal Model: Suitability for Use in Population Studies
Garry M Steil;
Garry M Steil
Metabolic Research Unit, Department of Physiology and Biophysics, University of Southern California Medical School
Los Angeles, California
Novo-Nordisk Research Institute
Copenhagen, Denmark
Veterans Affairs Medical Center
Seattle, Washington
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Aage Volund;
Aage Volund
Metabolic Research Unit, Department of Physiology and Biophysics, University of Southern California Medical School
Los Angeles, California
Novo-Nordisk Research Institute
Copenhagen, Denmark
Veterans Affairs Medical Center
Seattle, Washington
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Steven E Kahn;
Steven E Kahn
Metabolic Research Unit, Department of Physiology and Biophysics, University of Southern California Medical School
Los Angeles, California
Novo-Nordisk Research Institute
Copenhagen, Denmark
Veterans Affairs Medical Center
Seattle, Washington
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Richard N Bergman
Richard N Bergman
Metabolic Research Unit, Department of Physiology and Biophysics, University of Southern California Medical School
Los Angeles, California
Novo-Nordisk Research Institute
Copenhagen, Denmark
Veterans Affairs Medical Center
Seattle, Washington
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Address correspondence and reprint requests to Richard N. Bergman, PhD, Department of Physiology and Biophysics, USC Medical School, 2025 Zonal Avenue, Los Angeles, CA 90033.
Diabetes 1993;42(2):250–256
Article history
Received:
August 29 1991
Revision Received:
September 10 1992
Accepted:
September 10 1992
PubMed:
8425661
Citation
Garry M Steil, Aage Volund, Steven E Kahn, Richard N Bergman; Reduced Sample Number for Calculation of Insulin Sensitivity and Glucose Effectiveness From the Minimal Model: Suitability for Use in Population Studies. Diabetes 1 February 1993; 42 (2): 250–256. https://doi.org/10.2337/diab.42.2.250
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