Related Experiment Video
Updated: Mar 23, 2026
Characterization of Metabolic Status in Nonhuman Primates with the Intravenous Glucose Tolerance Test
Published on: November 13, 2016
Evaluation of Four Diagnostic Tests for Insulin Dysregulation in Adult Light-Breed Horses
L K Dunbar1, K A Mielnicki1, K A Dembek1
1Ohio State University College of Veterinary Medicine, Columbus, OH.
Background:
Several tests have been evaluated in horses for quantifying insulin dysregulation to support a diagnosis of equine metabolic syndrome. Comparing the performance of these tests in the same horses will provide clarification of their accuracy in the diagnosis of equine insulin dysregulation.
Objectives:
The aim of this study was to evaluate the agreement between basal serum insulin concentrations (BIC), the oral sugar test (OST), the combined glucose-insulin test (CGIT), and the frequently sampled insulin-modified intravenous glucose tolerance test (FSIGTT).
Animals:
Twelve healthy, light-breed horses.
Methods:
Randomized, prospective study. Each of the above tests was performed on 12 horses.
Results:
Minimal model analysis of the FSIGTT was considered the reference standard and classified 7 horses as insulin resistant (IR) and 5 as insulin sensitive (IS). In contrast, BIC and OST assessment using conventional cut-off values classified all horses as IS. Kappa coefficients, measuring agreement among BIC, OST, CGIT, and FSIGTT were poor to fair. Sensitivity of the CGIT (positive phase duration of the glucose curve >45 minutes) was 85.7% and specificity was 40%, whereas CGIT ([insulin]45 >100 μIU/mL) sensitivity and specificity were 28.5% and 100%, respectively. Area under the glucose curve (AUCg0-120 ) was significantly correlated among the OST, CGIT, and FSIGTT, but Bland-Altman method and Lin's concordance coefficient showed a lack of agreement.
Conclusions:
Current criteria for diagnosis of insulin resistance using BIC and the OST are highly specific but lack sensitivity. The CGIT displayed better sensitivity and specificity, but modifications may be necessary to improve agreement with minimal model analysis.
