Eichenlaub, Manuel, Khovanova, N. A., Gannon, Mary C., Nuttall, Frank Q. and Hattersley, John G. (2022) A glucose-only model to extract physiological information from postprandial glucose profiles in subjects with normal glucose tolerance. Journal of Diabetes Science and Technology, 16 (6). pp. 1532-1540. doi:10.1177/19322968211026978 ISSN 1932-2968.

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Abstract

Background:
Current mathematical models of postprandial glucose metabolism in people with normal and impaired glucose tolerance rely on insulin measurements and are therefore not applicable in clinical practice. This research aims to develop a model that only requires glucose data for parameter estimation while also providing useful information on insulin sensitivity, insulin dynamics and the meal-related glucose appearance (GA).

Methods:
The proposed glucose-only model (GOM) is based on the oral minimal model (OMM) of glucose dynamics and substitutes the insulin dynamics with a novel function dependant on glucose levels and GA. A Bayesian method and glucose data from 22 subjects with normal glucose tolerance are utilised for parameter estimation. To validate the results of the GOM, a comparison to the results of the OMM, obtained by using glucose and insulin data from the same subjects is carried out.

Results:
The proposed GOM describes the glucose dynamics with comparable precision to the OMM with an RMSE of 5.1 ± 2.3 mg/dL and 5.3 ± 2.4 mg/dL, respectively and contains a parameter that is significantly correlated to the insulin sensitivity estimated by the OMM (r = 0.7) Furthermore, the dynamic properties of the time profiles of GA and insulin dynamics inferred by the GOM show high similarity to the corresponding results of the OMM.

Conclusions:
The proposed GOM can be used to extract useful physiological information on glucose metabolism in subjects with normal glucose tolerance. The model can be further developed for clinical applications to patients with impaired glucose tolerance under the use of continuous glucose monitoring data.

Item Type:	Journal Article
Subjects:	Q Science > QP Physiology
Divisions:	Faculty of Science, Engineering and Medicine > Engineering > Engineering
Library of Congress Subject Headings (LCSH):	Glucose -- Metabolism -- Mathematical models, Insulin -- Absorption and adsorption -- Mathematical models
Journal or Publication Title:	Journal of Diabetes Science and Technology
Publisher:	Sage Publications, Inc.
ISSN:	1932-2968
Official Date:	November 2022
Dates:	Date Event November 2022 Published 5 July 2021 Available 20 May 2021 Accepted
Volume:	16
Number:	6
Page Range:	pp. 1532-1540
DOI:	10.1177/19322968211026978
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access (Creative Commons)
Date of first compliant deposit:	7 July 2021
Date of first compliant Open Access:	8 July 2021
RIOXX Funder/Project Grant:	Project/Grant ID RIOXX Funder Name Funder ID UNSPECIFIED University of Warwick http://dx.doi.org/10.13039/501100000741 UNSPECIFIED University Hospitals Coventry and Warwickshire NHS Trust http://viaf.org/viaf/152707181 EP/T013648/1 [EPSRC] Engineering and Physical Sciences Research Council http://dx.doi.org/10.13039/501100000266

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