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Modelling endogenous insulin concentration in type 2 diabetes during closed-loop insulin delivery
BACKGROUND: Closed-loop insulin delivery is an emerging treatment for type 1 diabetes (T1D) evaluated clinically and using computer simulations during pre-clinical testing. Efforts to make closed-loop systems available to people with type 2 diabetes (T2D) calls for the development of a new type of s...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4359432/ https://www.ncbi.nlm.nih.gov/pubmed/25889091 http://dx.doi.org/10.1186/s12938-015-0009-5 |
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author | Ruan, Yue Thabit, Hood Wilinska, Malgorzata E Hovorka, Roman |
author_facet | Ruan, Yue Thabit, Hood Wilinska, Malgorzata E Hovorka, Roman |
author_sort | Ruan, Yue |
collection | PubMed |
description | BACKGROUND: Closed-loop insulin delivery is an emerging treatment for type 1 diabetes (T1D) evaluated clinically and using computer simulations during pre-clinical testing. Efforts to make closed-loop systems available to people with type 2 diabetes (T2D) calls for the development of a new type of simulators to accommodate differences between T1D and T2D. Presented here is the development of a model of posthepatic endogenous insulin concentration, a component omitted in T1D simulators but key for simulating T2D physiology. METHODS: We evaluated six competing models to describe the time course of endogenous insulin concentration as a function of the plasma glucose concentration and time. The models were fitted to data collected in insulin-naive subjects with T2D who underwent two 24-h visits and were treated, in a random order, by either closed-loop insulin delivery or glucose-lowering oral agents. The model parameters were estimated using a Bayesian approach, as implemented in the WinBUGS software. Model selection criteria were used to identify the best model describing our clinical data. RESULTS: The selected model successfully described endogenous insulin concentration over 24 h in both study periods and provided plausible parameter estimates. Model-derived results were in concordance with a clinical finding which revealed increased posthepatic endogenous insulin concentration during the control study period (P < 0.05). The modelling results indicated that the excess amount of insulin can be attributed to the glucose-independent effect as the glucose-dependent effect was similar between visits (P > 0.05). CONCLUSIONS: A model to describe endogenous insulin concentration in T2D including components of posthepatic glucose-dependent and glucose-independent insulin secretion was identified and validated. The model is suitable to be incorporated in a simulation environment for evaluating closed-loop insulin delivery in T2D. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12938-015-0009-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4359432 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43594322015-03-15 Modelling endogenous insulin concentration in type 2 diabetes during closed-loop insulin delivery Ruan, Yue Thabit, Hood Wilinska, Malgorzata E Hovorka, Roman Biomed Eng Online Research BACKGROUND: Closed-loop insulin delivery is an emerging treatment for type 1 diabetes (T1D) evaluated clinically and using computer simulations during pre-clinical testing. Efforts to make closed-loop systems available to people with type 2 diabetes (T2D) calls for the development of a new type of simulators to accommodate differences between T1D and T2D. Presented here is the development of a model of posthepatic endogenous insulin concentration, a component omitted in T1D simulators but key for simulating T2D physiology. METHODS: We evaluated six competing models to describe the time course of endogenous insulin concentration as a function of the plasma glucose concentration and time. The models were fitted to data collected in insulin-naive subjects with T2D who underwent two 24-h visits and were treated, in a random order, by either closed-loop insulin delivery or glucose-lowering oral agents. The model parameters were estimated using a Bayesian approach, as implemented in the WinBUGS software. Model selection criteria were used to identify the best model describing our clinical data. RESULTS: The selected model successfully described endogenous insulin concentration over 24 h in both study periods and provided plausible parameter estimates. Model-derived results were in concordance with a clinical finding which revealed increased posthepatic endogenous insulin concentration during the control study period (P < 0.05). The modelling results indicated that the excess amount of insulin can be attributed to the glucose-independent effect as the glucose-dependent effect was similar between visits (P > 0.05). CONCLUSIONS: A model to describe endogenous insulin concentration in T2D including components of posthepatic glucose-dependent and glucose-independent insulin secretion was identified and validated. The model is suitable to be incorporated in a simulation environment for evaluating closed-loop insulin delivery in T2D. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12938-015-0009-5) contains supplementary material, which is available to authorized users. BioMed Central 2015-03-04 /pmc/articles/PMC4359432/ /pubmed/25889091 http://dx.doi.org/10.1186/s12938-015-0009-5 Text en © Ruan et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Ruan, Yue Thabit, Hood Wilinska, Malgorzata E Hovorka, Roman Modelling endogenous insulin concentration in type 2 diabetes during closed-loop insulin delivery |
title | Modelling endogenous insulin concentration in type 2 diabetes during closed-loop insulin delivery |
title_full | Modelling endogenous insulin concentration in type 2 diabetes during closed-loop insulin delivery |
title_fullStr | Modelling endogenous insulin concentration in type 2 diabetes during closed-loop insulin delivery |
title_full_unstemmed | Modelling endogenous insulin concentration in type 2 diabetes during closed-loop insulin delivery |
title_short | Modelling endogenous insulin concentration in type 2 diabetes during closed-loop insulin delivery |
title_sort | modelling endogenous insulin concentration in type 2 diabetes during closed-loop insulin delivery |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4359432/ https://www.ncbi.nlm.nih.gov/pubmed/25889091 http://dx.doi.org/10.1186/s12938-015-0009-5 |
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