Literature DB >> 15857229

Targeted glycemic reduction in critical care using closed-loop control.

J Geoffrey Chase1, Geoffrey M Shaw, Jessica Lin, Carmen V Doran, Chris Hann, Thomas Lotz, Graeme C Wake, Bob Broughton.   

Abstract

BACKGROUND: Critically ill patients are often hyperglycemic and extremely diverse in their dynamics. Consequently, fixed protocols and sliding scales can result in error and poor control. Tight glucose control has been shown to significantly reduce mortality in critical care. An improved physiological system model of the glucose-insulin dynamics of a critical care patient is used to develop an adaptive tight glucose control protocol that accounts for variable patient dynamics, and is verified in limited clinical trials.
METHODS: A physiologically based two-compartment system model that accounts for time-varying insulin sensitivity, time-varying endogenous glucose removal, and two saturation kinetics mechanisms is developed. A bolus-based adaptive control protocol is developed that monitors the physiological status of a critically ill patient, enabling tight glycemic regulation to preset glycemic targets. The model and protocol are verified in three, 5-h preliminary proof-of-concept clinical trials. Ethics approval was granted by the Canterbury Ethics Committee (Christchurch, New Zealand).
RESULTS: Preset glycemic targets are achieved with an average absolute error of 9%, with 75% of all targets achieved within the 7% measurement error. Absolute errors greater than 7% ranged from 17% to 21%.
CONCLUSIONS: Tight stepwise control was exhibited in all cases, and the adaptive system was able to match the model and observed patient dynamics. Most errors are associated with external perturbations such as drug therapies, or mismodeled parameters that can be easily adjusted with longer trials and/or more data per hour. The overall result is targeted stepwise tight glycemic regulation using insulin boluses.

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Year:  2005        PMID: 15857229     DOI: 10.1089/dia.2005.7.274

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  19 in total

1.  A minimal C-peptide sampling method to capture peak and total prehepatic insulin secretion in model-based experimental insulin sensitivity studies.

Authors:  Thomas Lotz; Uli Göltenbott; J Geoffrey Chase; Paul Docherty; Christopher E Hann
Journal:  J Diabetes Sci Technol       Date:  2009-07-01

2.  Model-based insulin sensitivity as a sepsis diagnostic in critical care.

Authors:  Amy Blakemore; Sheng-Hui Wang; Aaron Le Compte; Geoffrey M Shaw; Xing-Wei Wong; Jessica Lin; Thomas Lotz; Christopher E Hann; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2008-05

3.  Safety constraints in an artificial pancreatic beta cell: an implementation of model predictive control with insulin on board.

Authors:  Christian Ellingsen; Eyal Dassau; Howard Zisser; Benyamin Grosman; Matthew W Percival; Lois Jovanovic; Francis J Doyle
Journal:  J Diabetes Sci Technol       Date:  2009-05-01

Review 4.  Clinical need for continuous glucose monitoring in the hospital.

Authors:  Jeffrey I Joseph; Brian Hipszer; Boris Mraovic; Inna Chervoneva; Mark Joseph; Zvi Grunwald
Journal:  J Diabetes Sci Technol       Date:  2009-11-01

5.  Identification of intraday metabolic profiles during closed-loop glucose control in individuals with type 1 diabetes.

Authors:  Sami S Kanderian; Stu Weinzimer; Gayane Voskanyan; Garry M Steil
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

6.  Pilot study of the SPRINT glycemic control protocol in a Hungarian medical intensive care unit.

Authors:  Balazs Benyo; Attila Illyés; Noémi Szabó Némedi; Aaron J Le Compte; Attila Havas; Levente Kovacs; Liam Fisk; Geoffrey M Shaw; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2012-11-01

7.  Organ failure and tight glycemic control in the SPRINT study.

Authors:  J Geoffrey Chase; Christopher G Pretty; Leesa Pfeifer; Geoffrey M Shaw; Jean-Charles Preiser; Aaron J Le Compte; Jessica Lin; Darren Hewett; Katherine T Moorhead; Thomas Desaive
Journal:  Crit Care       Date:  2010-08-12       Impact factor: 9.097

8.  Overview of glycemic control in critical care: relating performance and clinical results.

Authors:  J Geoffrey Chase; Christopher E Hann; Geoffrey M Shaw; Jason Wong; Jessica Lin; Thomas Lotz; Aaron Lecompte; Timothy Lonergan
Journal:  J Diabetes Sci Technol       Date:  2007-01

9.  A benchmark data set for model-based glycemic control in critical care.

Authors:  J Geoffrey Chase; Aaron LeCompte; Geoffrey M Shaw; Amy Blakemore; Jason Wong; Jessica Lin; Christopher E Hann
Journal:  J Diabetes Sci Technol       Date:  2008-07

10.  The impact of parameter identification methods on drug therapy control in an intensive care unit.

Authors:  Christopher E Hann; J Geoffrey Chase; Michael F Ypma; Jos Elfring; Noorhafiz Mohd Nor; Piers Lawrence; Geoffrey M Shaw
Journal:  Open Med Inform J       Date:  2008-05-27
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