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A HIGHLY CORRELATED METHOD TO ASSESS INSULIN RESISTANCE IN BROAD POPULATIONS T Lotz 1 J G Chase 1, KA McAuley 2, GM Shaw 3, CE Hann 1, JI Mann 2 1 Department.

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Presentation on theme: "A HIGHLY CORRELATED METHOD TO ASSESS INSULIN RESISTANCE IN BROAD POPULATIONS T Lotz 1 J G Chase 1, KA McAuley 2, GM Shaw 3, CE Hann 1, JI Mann 2 1 Department."— Presentation transcript:

1 A HIGHLY CORRELATED METHOD TO ASSESS INSULIN RESISTANCE IN BROAD POPULATIONS T Lotz 1 J G Chase 1, KA McAuley 2, GM Shaw 3, CE Hann 1, JI Mann 2 1 Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand 2 Edgar National Centre for Diabetes Research, University of Otago, Dunedin, New Zealand 3 Department of Intensive Medicine, Christchurch Hospital, Christchurch, New Zealand

2 The Problem Insulin resistance is a major risk factor in the development of type-2 Diabetes and cardiovascular disease Early and regular monitoring is crucial to assess effects of intervention Accurate assessment is difficult and stressful with current methods

3 Current methods ACCURACYSTRESS + LENGTH + COST CLAMP 3-6 hours IVGTT 2-4 hours HOMA 10 mins GOAL FOR NEW TEST Can we be accurate, yet simple and short??

4 Insulin Glucose Short, simple, no steady state necessary (30-60 min) Physiological doses of glucose+insulin 1.Measure glucose, insulin, C- peptide 2.Fit model to data 3.Determine S I from model  Physiological model necessary! 051015203025 Glucose profile glucose Concept

5 Model of Glucose and Insulin Kinetics PLASMA INTERSTITIAL FLUID KIDNEYS LIVER diffusion CELLS PANCREAS nCnC nKnK nLnL nInI u en u ex GLUCOSE (Lotz et al ICBME 2005)

6 Model validation on ‘gold-standard’ clamp test High correlations at steady and transient states ISI vs. … r (95% CI) S I (steady state)0.98 (0.97-0.99) S I (transient)0.94 (0.91-0.96) Log-HOMA-0.31 r=0.98 transient steady

7 Test simulation Simulated population from clamp data (N=195) Correlation r=0.93 between model S I and clamp ISI during 40 minute transient test Model captures dynamics of insulin and glucose within measurement error Low, physiological dosing  Increased safety and accuracy

8 Conclusions Simple model-based dose response test to assess insulin resistance Physiological dosing, short duration, cost efficient, yet highly accurate! Simulation results correlate r=0.93 with ‘gold standard’ clamp test Potential for application in a clinical setting

9 Acknowledgements – Questions? Geoff ChaseGeoff Shaw Dominic Lee Steen Andreassen Jim Mann Kirsten McAuley Jessica LinChris HannJason Wong


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