The oral glucose tolerance test (OGTT) minimal model analysis by Cobelli et al. obtains estimates of insulin sensitivity (SI) based on mathematical models that are highly concordant with the euglycemic clamp, the gold standard for estimation SI. This model requires a minimum of 7 blood samples during the 2-hour OGTT. However, in many OGTT studies, the number of samples is below the number that permits the estimation of SI. One way to address (overcome) this issue is by pooling sparsely sampled data (<7 samples) from a specific cohort to obtain population estimates of parameters of SI. Here we present a novel methodology of estimating population SI using sparsely-sampled OGTT protocol. A cohort of 6 African American subjects (3 Female/ 3 Male) without a known history of T2D underwent 75-gm OGTTs with 6 samples performed at 0, 15, 30, 60, 90 and 120 minutes. The population SI was estimated concurrently fitting the data from all subjects. We obtained population estimates of SI using from 3 to 6 samples per subject. SI estimates for each subject were also calculated. Sparse-sampling population estimated SI varied from SI=4.74±.75 10-4.(mu/l)-1.min-1 for 4 samples to SI= 6.40±2.40 10-4.(mu/l)-1.min-1 for 3 samples. The individual estimates of SI had a mean of SI= 4.72±2.43 10-4.(mu/l)-1.min-1. SI obtained with the sparse-sampling methodology did not differ from the mean individual estimates of SI. We conclude that Sparse-sampling estimation of SI (<7 samples) is a useful tool for estimation of population parameters of SI where there are not enough observations per subject to estimate individual insulin sensitivity. This methodology will provide better phenotyping of insulin sensitivity for studies where previously more crude measures were used.


D. Stefanovski: None. G.E. Umpierrez: Research Support; Self; Sanofi US, Merck & Co., Inc., Novo Nordisk Inc., AstraZeneca. Advisory Panel; Self; Sanofi, Intarcia Therapeutics, Inc. P. Vellanki: Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc.. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., AstraZeneca.

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