Linked Life Data

21439721

Source:http://linkedlifedata.com/resource/pubmed/id/21439721

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2011-4-18
pubmed:abstractText
Previous studies have shown that effective quantification of the cyclic variation of myocardial ultrasonic backscatter over the heart cycle might provide a non-invasive technique for identifying the early onset of cardiac abnormalities. These studies have demonstrated the potential for measurements of the magnitude and time delay of cyclic variation for identifying early onset of disease. The goal of this study was to extend this approach by extracting additional parameters characterizing the cyclic variation in an effort to better assess subtle changes in myocardial properties in asymptomatic subjects with type 2 diabetes. Echocardiographic images were obtained on a total of 43 age-matched normal control subjects and 100 type 2 diabetics. Cyclic variation data were generated by measuring the average level of ultrasonic backscatter over the heart cycle within a region of interest placed in the posterior wall of the left ventricle. Cyclic variation waveforms were modeled as piecewise linear functions, and quantified using a novel Bayesian parameter estimation method. Magnitude, rise time and slew rate parameters were extracted from models of the data. The ability of each of these parameters to distinguish between normal and type 2 diabetic subjects, and between subjects grouped by glycated hemoglobin (HbA1c) was compared. Results suggest a significant improvement in using measurements of the rise time and slew rate parameters of cyclic variation to differentiate (P < 0.001) the hearts of patients segregated based on widely employed indices of diabetic control compared to differentiation based on the magnitude of cyclic variation.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1879-291X
pubmed:author
pubmed:copyrightInfo
Copyright © 2011 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.
pubmed:issnType
Electronic
pubmed:volume
37
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
805-12
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Bayesian parameter estimation for characterizing the cyclic variation of echocardiographic backscatter to assess the hearts of asymptomatic type 2 diabetes mellitus subjects.
pubmed:affiliation
Laboratory for Ultrasonics, Department of Physics, Washington University, St. Louis, MO, USA.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural