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

Steil, Garry M, Volund, Aage, Kahn, Steven E, Bergman, Richard N·1993·Diabetes

Abstract

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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Cites

  • Quantitative estimation of insulin sensitivity.

    Bergman, R. N., Ider, Y. Z., Bowden, C. R., & Cobelli, C. (1979) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.1979.236.6.e667 · Cited by 1,874 · cited 1×

    “These equations are based on three key physiological assumptions (17): 1) glucose inhibits its own production and increases its own utilization in proportion to its concentration in plasma; 2) insulin synergizes these effects of glucose; and 3) insulin effect is proportional to its concentration in a remote compartmen…”
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Metadata

Authors
Steil, G. M., Volund, A., Kahn, S. E., & Bergman, R. N.
Venue
Diabetes
Published
1993-02-01
Volume
42
Issue
2
Pages
250-256
ISSN
  • 0012-1797 (ISSN-L)
  • 1939-327X
OpenAlex
W2028414281
Cited by
215
References
1
FWCI
4.60
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Reduced Sample Number for Calculation of Insulin Sensitivity and Glucose Effectiveness From the Minimal Model: Suitability for Use in Population Studies. https://app.cochat.ai/papers/10.2337/diab.42.2.250
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Steil, G. M., Volund, A., Kahn, S. E., & Bergman, R. N. (1993). Reduced Sample Number for Calculation of Insulin Sensitivity and Glucose Effectiveness From the Minimal Model: Suitability for Use in Population Studies. Diabetes. https://doi.org/10.2337/diab.42.2.250

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