Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
A dual-energy X-ray absorptiometry (DXA) application to measure visceral adipose tissue (VAT) in the android region of a total body DXA scan has recently been developed. This new application, CoreScan, has been validated on the Lunar iDXA (GE Healthcare, Madison, WI) densitometer against volumetric computed tomography. The geometric assumptions underlying the CoreScan model are the same on the Prodigy (GE Healthcare, Madison, WI) densitometer. However, differences between the peak X-ray voltage and detector array configurations may lead to differences in VAT quantification. The purpose of this study was to evaluate the agreement of Prodigy and iDXA CoreScan values and to characterize differences in VAT precision between the instruments. Data from volunteers with paired Prodigy and iDXA measurements were used to define empirical adjustments to the VAT algorithm parameters (n=59) and validate performance on Prodigy (n=62). Prodigy VAT measurements were highly correlated to iDXA (r=0.984). The mean of the Prodigy-iDXA VAT volume differences was -13.8cm³ with a 95% confidence interval of -45 to +17cm³. The Bland-Altman 95% limits of agreement for the 2 methods were -252 to +224cm³. Measurement of short-term precision showed that measurement error variance on iDXA was smaller (p<0.01) than Prodigy (coefficient of variance: 7.3% vs 9.8%). Precision results are in agreement with previous reports on the differences between Prodigy and iDXA for body composition measures. Prodigy and iDXA measures of VAT are similar, but the lower precision of the Prodigy may require investigators to target larger changes in VAT.
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Source |
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http://dx.doi.org/10.1016/j.jocd.2012.09.002 | DOI Listing |
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