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Diagnostic accuracy of 64 slice multidetector coronary computed tomographic angiography in left ventricular systolic dysfunction
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https://doi.org/10.1016/j.ijcha.2015.04.007Abstract
Background
Detecting coronary artery disease (CAD) is pivotal in etiologic assessment and management of left ventricular (LV) systolic dysfunction. Only a limited number of studies have specifically addressed the accuracy of coronary computed tomographic angiography (CCTA) in detection/exclusion of CAD in patients with LV systolic dysfunction.Methods
We included patients who were referred for CCTA and invasive coronary angiography within 6 months of each other because of chest pain, either as part of clinical work-up in two Los Angeles medical centers from September 2006 to May 2010 or as part of the multicenter ACCURACY trial. Sensitivity, specificity, positive and negative predictive value, and likelihood ratios of 64 slice multidetector CCTA against coronary angiography were calculated.Results
Five hundred and thirty-seven patients were included: 228 (42.5%) were women, mean age was 62 ± 12 years, 82 (15.3%) had LV systolic dysfunction (defined by LVEF < 50%). On a patient-based model, the sensitivity of CCTA to detect 50% and 70% coronary lesions was excellent across all LVEF-derived cohorts, ranging from 92% to 100%. The negative predictive value was similarly excellent, ranging from 88% to 100%. CCTA was fairly specific for CAD, with specificity ranging from 83% to 93%, and positive predictive value from 81% to 92%. There was no significant between-group difference for any of the accuracy measures for detecting coronary stenosis at 50% or 70% cutoff.Conclusion
Sixty-four slice multidetector CCTA is a very sensitive and fairly specific noninvasive diagnostic procedure for detecting coronary stenosis in patients with chest pain regardless of LV systolic function at presentation.Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
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