Document Detail


Reduced sampling schedule for the glucose minimal model: importance of Bayesian estimation.
MedLine Citation:
PMID:  16144816     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The minimal model (MM) of glucose kinetics during an intravenous glucose tolerance test (IVGTT) is widely used in clinical studies to measure metabolic indexes such as glucose effectiveness (S(G)) and insulin sensitivity (S(I)). The standard (frequent) IVGTT sampling schedule (FSS) for MM identification consists of 30 points over 4 h. To facilitate clinical application of the MM, reduced sampling schedules (RSS) of 13-14 samples have also been derived for normal subjects. These RSS are especially appealing in large-scale studies. However, with RSS, the precision of S(G) and S(I) estimates deteriorates and, in certain cases, becomes unacceptably poor. To overcome this difficulty, population approaches such as the iterative two-stage (ITS) approach have been recently proposed, but, besides leaving some theoretical issues open, they appear to be oversized for the problem at hand. Here, we show that a Bayesian methodology operating at the single individual level allows an accurate determination of MM parameter estimates together with a credible measure of their precision. Results of 16 subjects show that, in passing from FSS to RSS, there are no significant changes of point estimates in nearly all of the subjects and that only a limited deterioration of parameter precision occurs. In addition, in contrast with the previously proposed ITS method, credible confidence intervals (e.g., excluding negative values) are obtained. They can be crucial for a subsequent use of the estimated MM parameters, such as in classification, clustering, regression, or risk analysis.
Authors:
Paolo Magni; Giovanni Sparacino; Riccardo Bellazzi; Claudio Cobelli
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2005-09-06
Journal Detail:
Title:  American journal of physiology. Endocrinology and metabolism     Volume:  290     ISSN:  0193-1849     ISO Abbreviation:  Am. J. Physiol. Endocrinol. Metab.     Publication Date:  2006 Jan 
Date Detail:
Created Date:  2005-12-12     Completed Date:  2006-02-27     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  100901226     Medline TA:  Am J Physiol Endocrinol Metab     Country:  United States    
Other Details:
Languages:  eng     Pagination:  E177-E184     Citation Subset:  IM    
Affiliation:
Dipartimento di Informatica e Sistemica, Università degli Studi di Padova, I-35131 Padua, Italy.
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MeSH Terms
Descriptor/Qualifier:
Adult
Algorithms
Bayes Theorem*
Blood Glucose / metabolism*
Confidence Intervals
Glucose Tolerance Test / methods*,  statistics & numerical data
Humans
Insulin / blood
Kinetics
Models, Biological*
Chemical
Reg. No./Substance:
0/Blood Glucose; 11061-68-0/Insulin

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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