Linked Life Data

2650564

Source:http://linkedlifedata.com/resource/pubmed/id/2650564

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4 Pt 1
pubmed:dateCreated
1989-5-18
pubmed:abstractText
The minimal models of glucose-insulin kinetics were used to analyze sets of data obtained from human subjects and dogs during frequently sampled intravenous glucose tolerance tests (FSIGTs). Analysis of some data sets from both species resulted in poor identification of parameters. To improve the parameter resolution, the information base on which the parameters are estimated was enlarged. This was accomplished by incorporating into the analysis 1) glucose data obtained between 0 and 8 min of the FSIGT and some of the insulin data obtained prior to the insulin peak and 2) a second set of FSIGT data for each individual obtained during a physiological perturbation. As a result, data analysis was considerably enhanced, with parameter fractional standard deviation being routinely reduced to less than 0.5. Analysis of stimulated data with noise levels for glucose and insulin set between 0.05 and 0.15 confirmed the improvement in parameter estimates. This modified approach to analysis of FSIGTs therefore consistently leads to well-defined kinetic descriptions of experimental data in various situations and supports the usefulness of the minimal model in examining the complex interplay between the parameters that influence overall glucose tolerance.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0002-9513
pubmed:author
pubmed:issnType
Print
pubmed:volume
256
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
E524-35
pubmed:dateRevised
2011-11-17
pubmed:meshHeading
pubmed:year
1989
pubmed:articleTitle
Alternative method for minimal model analysis of intravenous glucose tolerance data.
pubmed:affiliation
Animal Research Institute, Department of Agriculture and Rural Affairs, Werribee, Australia.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't