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BACKGROUND: Increased glycemic variability is associated with an increase risk of adverse clinical outcomes in diabetes. Central to the understanding of diabetes is glucose homeostasis. "Good" homeostasis is equated to low glycemic variability, and "poor" homeostasis is linked to greater glycemic variability. We have, therefore, developed a method with the aim to objectively quantify the domain of glucose-insulin homeostasis. We have termed this method as Observed Variability And Lability (OVAL). METHOD: Blood samples for the measurement of glucose and insulin concentrations were acquired every 2 min for 120 min from 12 patients with type 2 diabetes mellitus [T2DM; median (range) age 35 (25-47) years and duration of diabetes 7 (2-9) years receiving oral hypoglycemic treatment] and 27 controls [aged 38(30-53) years] with an equal split of genders and equal distribution of body mass indexes. The insulin-glucose time variant data form the boundaries of OVAL, defined as the ellipse enclosing the 95% confidence intervals of the insulin and glucose concentrations plotted on an x-y scatter graph and normalized to ensure equal weighting of insulin and glucose. RESULTS: Less precise OVAL homeostasis was observed in subjects with T2DM, by a factor of 4, in comparison with controls [OVAL, T2DM 7.8(3.8) versus controls 1.9(1.0); p = .0003]. The assessment remained statistically robust (p < .001) with increased sampling intervals up to 8 min. CONCLUSION: The OVAL model is a robust method for measuring glucose-insulin homeostasis in controls and T2DM subjects (available online at http://www.oval-calc.co.uk). Deranged glucose-insulin homeostasis is the hallmark of diabetes and OVAL has the capacity to quantify in the fasting state.

Original publication

DOI

10.1177/193229681300700308

Type

Journal article

Journal

J Diabetes Sci Technol

Publication Date

01/05/2013

Volume

7

Pages

640 - 645

Keywords

Adult, Blood Glucose, Diabetes Mellitus, Type 2, Fasting, Female, Homeostasis, Humans, Insulin, Male, Middle Aged, Models, Statistical