Literature DB >> 23439178

Multilevel model of type 1 diabetes mellitus patients for model-based glucose controllers.

Winston Garcia-Gabin1, Elling W Jacobsen.   

Abstract

BACKGROUND: Glucose homeostasis is the result of complex interactions across different biological levels. This multilevel characteristic should be considered when analyzing and designing closed-loop glucose control algorithms. Classic control schemes use only a pharmacokinetic-pharmacodynamic (PKPD) perspective to describe the gluco-regulatory system.
METHODS: A multilevel model combining a PKPD model with an insulin signaling model is proposed for patients with type 1 diabetes mellitus T1DM (T1DM). The PKPD Dalla Man model for T1DM is expanded to include an intracellular level involving insulin signaling to control glucose uptake through glucose transporter type 4 (GLUT4) translocation. A model-based controller is then designed and used as an example to illustrate the feasibility of the proposal.
RESULTS: Two significant results were obtained for the controller explicitly utilizing multilevel information. No hypo-glycemic events were registered and an excellent performance for interpatient variability was achieved. Controller performance was evaluated using two indexes. The glucose was kept inside the range (70-180) mg/dl more than 99% of the time, and the intrapatient variability measured using control variability grid analysis was solid with 90% of the population inside the target zone.
CONCLUSIONS: Multilevel models open new possibilities for designing glucose control algorithms. They allow controllers to take into account variables that have a strong influence on glucose homeostasis. A model-based controller was used for demonstrating how improved knowledge of the multilevel nature of diabetes increases the robustness and performance of glucose control algorithms. Using the proposed multi-level approach, a reduction of the hypoglycemic risk and robust behaviour for intrapatient variability was demonstrated.
© 2012 Diabetes Technology Society.

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Year:  2013        PMID: 23439178      PMCID: PMC3692234          DOI: 10.1177/193229681300700125

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  18 in total

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2.  A closed-loop artificial pancreas using model predictive control and a sliding meal size estimator.

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3.  Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: preliminary studies in Padova and Montpellier.

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Journal:  J Diabetes Sci Technol       Date:  2009-09-01

4.  A hierarchical whole-body modeling approach elucidates the link between in Vitro insulin signaling and in Vivo glucose homeostasis.

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5.  The hot IVGTT two-compartment minimal model: indexes of glucose effectiveness and insulin sensitivity.

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Journal:  Am J Physiol       Date:  1997-11

Review 6.  Roles of circadian rhythmicity and sleep in human glucose regulation.

Authors:  E Van Cauter; K S Polonsky; A J Scheen
Journal:  Endocr Rev       Date:  1997-10       Impact factor: 19.871

Review 7.  Hypoglycemia is the limiting factor in the management of diabetes.

Authors:  P E Cryer
Journal:  Diabetes Metab Res Rev       Date:  1999 Jan-Feb       Impact factor: 4.876

8.  Partitioning glucose distribution/transport, disposal, and endogenous production during IVGTT.

Authors:  Roman Hovorka; Fariba Shojaee-Moradie; Paul V Carroll; Ludovic J Chassin; Ian J Gowrie; Nicola C Jackson; Romulus S Tudor; A Margot Umpleby; Richard H Jones
Journal:  Am J Physiol Endocrinol Metab       Date:  2002-05       Impact factor: 4.310

9.  Meal simulation model of the glucose-insulin system.

Authors:  Chiara Dalla Man; Robert A Rizza; Claudio Cobelli
Journal:  IEEE Trans Biomed Eng       Date:  2007-10       Impact factor: 4.538

10.  A molecular mathematical model of glucose mobilization and uptake.

Authors:  Weijiu Liu; ChingChun Hsin; Fusheng Tang
Journal:  Math Biosci       Date:  2009-08-03       Impact factor: 2.144

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  1 in total

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  1 in total

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