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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
Objective: The main aim of the study was, to estimate the impact of perfusion defects including significantly depleted areas of varying size on gated perfusion SPECT (GPS) determined ejection fraction (EF) measurements in comparison to radionuclide ventriculography (RVG). A secondary objective was the evaluation of the GPS-RVG agreement of EF in patients with normal and deteriorated left ventricular function, separately.
Methods: Fifty-nine patients having perfusion defects including at least one segment with no visible tracer uptake in rest myocardial GPS related to myocardial infarction (older than 15 days) were studied. Myocardial perfusion was visually analyzed using a 17 segment-model, on a five-point (0-4) grading system in which Grade-4 (0-9% maximal uptake) represents cold defects. The patients with >or=4 adjacent, with 2-3 adjacent and with 1 single cold segments were named as Group1(GR1), Group2(GR2) and Group3(GR3), respectively. Secondly, the patients were re-grouped according to RVG-EF values. (Group A: patients with EF<50%; Group B: patients with EF>or=50%). In each group, the GPS-EFs were compared with RVG performed within one week and also the variations of GPS-RVG EF differences among the groups were statistically analyzed.
Results: In overall (r=0.86) and in each subgroup, EFs obtained by GPS were well correlated with RVG. However, in overall (difference mean EF% [dEF%]=4.6+/-6.7, p<0.001) as well as in subgroup evaluation, GPS significantly (p<0.005) underestimated EF. There was no statistically significant difference in GPS-RVG EF variations between GR1, GR2 and GR3 (p>0.05). The RVG-mean differences and RVG-correlation coefficients calculated for GR1,GR2 and GR3 were dEF%=3.1+/-4.6, r=0.85; dEF%=3.7+/-6.03, r=0.80 and dEF%=6.2+/-8.03, r=0.79, respectively. Mean dEF% was statistically higher in group-B than group-A (mean difference of dEF%=4,2, p<0.05). In group-A, GPS-EF values were better agreed with RVG (dEF%=3.34, r=0.75) than in group-B (dEF%=7.52, r=0.53).
Conclusion: The stability of the calculation algorithm of QGS in EF calculation of patients with large depleted infarct areas could be confirmed. The agreement of GPS determined EF is higher in patients having myocardial integrity loss and left ventricular dysfunction.
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Source |
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http://dx.doi.org/10.1007/s10554-005-9024-0 | DOI Listing |
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