Literature DB >> 16800755

Transient and steady-state euglycemic clamp validation of a model for glycemic control and insulin sensitivity testing.

Thomas F Lotz1, J Geoffrey Chase, Kirsten A McAuley, Dominic S Lee, Jessica Lin, Christopher E Hann, Jim I Mann.   

Abstract

BACKGROUND: There is an urgent need for a simple and accurate measure of insulin sensitivity to diagnose insulin resistance in the general population and quantify changes due to clinical intervention. A new physiological control model of glucose and insulin metabolism is validated with the euglycemic-hyperinsulinemic clamp during steady and transient states.
METHODS: The data consist of n = 60 (15 lean, 15 overweight, 15 obese, and 15 morbidly obese) euglycemic-hyperinsulinemic clamp trials performed on normoglycemic insulin-resistant individuals. The glucose and insulin model is fitted using an integral-based method. Correlations between clamp-derived insulin sensitivity index (ISI) and the model's insulin sensitivity parameter (SI) are obtained during steady and transient states. Results are compared with log-homeostasis model assessment (HOMA), a widely used fasting surrogate for insulin sensitivity.
RESULTS: Correlation between model-based insulin sensitivity, SI, and ISIG (ISI normalized by steady-state glucose) is r = 0.99 (n = 60) at steady state and r = 0.97 at transient state, respectively. Correlations did not significantly change across subgroups, with narrow 95% confidence intervals. Log-HOMA correlations are r=-0.72 to SI and r=-0.71 to ISIG for the overall population but are significantly lower in the subgroups, with wide 95% confidence intervals.
CONCLUSIONS: The model-based insulin sensitivity parameter, SI, highly correlates to ISIG in all subgroups, even when only considering a transient state. The high correlation of SI offers the potential for a short, simple yet highly correlated, model-based assessment of insulin sensitivity that is not currently available.

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Year:  2006        PMID: 16800755     DOI: 10.1089/dia.2006.8.338

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


  13 in total

1.  Characterisation of the iterative integral parameter identification method.

Authors:  Paul D Docherty; J Geoffrey Chase; Timothy David
Journal:  Med Biol Eng Comput       Date:  2011-12-29       Impact factor: 2.602

2.  Blood glucose controller for neonatal intensive care: virtual trials development and first clinical trials.

Authors:  Aaron Le Compte; J Geoffrey Chase; Adrienne Lynn; Chris Hann; Geoffrey Shaw; Xing-Wei Wong; Jessica Lin
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

3.  What makes tight glycemic control tight? The impact of variability and nutrition in two clinical studies.

Authors:  Fatanah Suhaimi; Aaron Le Compte; Jean-Charles Preiser; Geoffrey M Shaw; Paul Massion; Regis Radermecker; Christopher G Pretty; Jessica Lin; Thomas Desaive; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2010-03-01

4.  Variability of insulin sensitivity during the first 4 days of critical illness: implications for tight glycemic control.

Authors:  Christopher G Pretty; Aaron J Le Compte; J Geoffrey Chase; Geoffrey M Shaw; Jean-Charles Preiser; Sophie Penning; Thomas Desaive
Journal:  Ann Intensive Care       Date:  2012-06-15       Impact factor: 6.925

5.  Validation of a model-based virtual trials method for tight glycemic control in intensive care.

Authors:  J Geoffrey Chase; Fatanah Suhaimi; Sophie Penning; Jean-Charles Preiser; Aaron J Le Compte; Jessica Lin; Christopher G Pretty; Geoffrey M Shaw; Katherine T Moorhead; Thomas Desaive
Journal:  Biomed Eng Online       Date:  2010-12-14       Impact factor: 2.819

6.  The Impact of Exogenous Insulin Input on Calculating Hepatic Clearance Parameters.

Authors:  Alexander D McHugh; J Geoffrey Chase; Jennifer L Knopp; Jennifer J Ormsbee; Diana G Kulawiec; Troy L Merry; Rinki Murphy; Peter R Shepherd; Hannah J Burden; Paul D Docherty
Journal:  J Diabetes Sci Technol       Date:  2021-01-21

7.  Untangling glycaemia and mortality in critical care.

Authors:  Vincent Uyttendaele; Jennifer L Dickson; Geoffrey M Shaw; Thomas Desaive; J Geoffrey Chase
Journal:  Crit Care       Date:  2017-06-24       Impact factor: 9.097

8.  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

9.  Estimating Enhanced Endogenous Glucose Production in Intensive Care Unit Patients with Severe Insulin Resistance.

Authors:  Anane Yahia; Ákos Szlávecz; Jennifer L Knopp; Normy Norfiza Abdul Razak; Asma Abu Samah; Geoff Shaw; J Geoffrey Chase; Balazs Benyo
Journal:  J Diabetes Sci Technol       Date:  2021-06-02

10.  Implementation and evaluation of the SPRINT protocol for tight glycaemic control in critically ill patients: a clinical practice change.

Authors:  J Geoffrey Chase; Geoffrey Shaw; Aaron Le Compte; Timothy Lonergan; Michael Willacy; Xing-Wei Wong; Jessica Lin; Thomas Lotz; Dominic Lee; Christopher Hann
Journal:  Crit Care       Date:  2008-04-16       Impact factor: 9.097

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