Title :
Estimating Insulin Sensitivity from glucose levels only: Use of a non-linear mixed effects approach and Bayesian estimation
Author :
Yates, James W. T. ; Watson, Edmund M.
Author_Institution :
AstraZeneca R&D, Macclesfield, UK
Abstract :
Insulin Sensitivity is an important parameter for the diagnosis and management of Diabetes. It is derived for a particular patient using data derived from some glucose challenge tests using measured glucose and insulin levels at various times. Whilst a useful approach, deriving insulin sensitivities to inform insulin dosing in other settings such as Intensive Care Units can be more challenging - especially as insulin levels have to be assayed in a laboratory, not at the bedside. This paper investigates an approach to measure insulin sensitivity from glucose levels only. Estimates of mean and between individual parameter variances are used to derive conditional estimates of insulin sensitivity. The method is demonstrated to perform reasonably well, with conditional estimates comparing well with estimates derived from insulin data as well.
Keywords :
Bayes methods; diseases; medical diagnostic computing; patient treatment; sugar; Bayesian estimation; diabetes diagnosis; diabetes management; glucose level; insulin dosing; insulin level; insulin sensitivity; intensive care units; nonlinear mixed effect; Bayesian Estimation; Biomedical Model; Glucose; Insulin; Mixed-effects;
Conference_Titel :
Control 2010, UKACC International Conference on
Conference_Location :
Coventry
Electronic_ISBN :
978-1-84600-038-6
DOI :
10.1049/ic.2010.0456