A Physiology-Based Model Describing Heterogeneity in Glucose Metabolism: The Core of the Eindhoven Diabetes Education Simulator (E-DES). (18th December 2014)

• Record Type: Journal Article
• Authors: Maas, Anne H.; Rozendaal, Yvonne J. W.; van Pul, Carola; Hilbers, Peter A. J.; Cottaar, Ward J.; Haak, Harm R.; van Riel, Natal A. W.
• Is Part Of: Journal of diabetes science and technology. Volume 9:Number 2(2015:Mar.)
• Page Start: 282
• Page End: 292
• Publication Date: 2014-12-18
• Subjects: diabetes -- education -- model -- simulator -- parameter estimation -- heterogeneity; Diabetes -- Periodicals; Medical technology -- Periodicals; Diabetes Mellitus -- Periodicals; 616.462005
• DOI: 10.1177/1932296814562607
• Languages: English
• ISSNs: 1932-2968

Abstract

Background: Current diabetes education methods are costly, time-consuming, and do not actively engage the patient. Here, we describe the development and verification of the physiological model for healthy subjects that forms the basis of the Eindhoven Diabetes Education Simulator (E-DES). E-DES shall provide diabetes patients with an individualized virtual practice environment incorporating the main factors that influence glycemic control: food, exercise, and medication. Method: The physiological model consists of 4 compartments for which the inflow and outflow of glucose and insulin are calculated using 6 nonlinear coupled differential equations and 14 parameters. These parameters are estimated on 12 sets of oral glucose tolerance test (OGTT) data (226 healthy subjects) obtained from literature. The resulting parameter set is verified on 8 separate literature OGTT data sets (229 subjects). The model is considered verified if 95% of the glucose data points lie within an acceptance range of ±20% of the corresponding model value. Results: All glucose data points of the verification data sets lie within the predefined acceptance range. Physiological processes represented in the model include insulin resistance and β-cell function. Adjusting the corresponding parameters allows to describe heterogeneity in the data and shows the capabilities of this model for individualization. Conclusion: We have verified the physiological model of the E-DES for healthy subjects. Heterogeneity of the data has successfully been modeled by adjusting the 4 parameters describing insulin resistance and β-cell function. Our model will form the basis of a simulator providing individualized education on glucose control.