A Physiology-Based Model Describing Heterogeneity in Glucose Metabolism

Author:

Maas Anne H.123,Rozendaal Yvonne J. W.2,van Pul Carola4,Hilbers Peter A. J.2,Cottaar Ward J.3,Haak Harm R.156,van Riel Natal A. W.1

Affiliation:

1. Department of Internal Medicine, Máxima Medical Center Eindhoven, Eindhoven, Netherlands

2. Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands

3. Stan Ackermans Institute - Design of Technology and Instrumentation, Eindhoven University of Technology, Eindhoven, Netherlands

4. Department of Clinical Physics, Máxima Medical Center Veldhoven, Veldhoven, Netherlands

5. Department of Internal Medicine, Division of General Medicine, Section Acute Medicine, Maastricht University Medical Centre, Maastricht, Netherlands

6. Department of Health Services Research and CAPHRI School for Public Health and Primary Care, Maastricht University, Eindhoven, Netherlands

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.

Publisher

SAGE Publications

Subject

Biomedical Engineering,Bioengineering,Endocrinology, Diabetes and Metabolism,Internal Medicine

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