CTCA for detection of significant coronary artery disease in routine TAVI work-up

  • van den Boogert T
  • Vendrik J
  • Claessen B
  • et al.
N/ACitations
Citations of this article
9Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Transcatheter aortic valve implantation (TAVI) has evolved to standard treatment of severe aortic stenosis in patients with an intermediate to high surgical risk. Computed tomography coronary angiography (CTCA) could partially replace invasive coronary angiography to diagnose significant coronary artery disease in the work-up for TAVI. A literature search was performed in MEDLINE and EMBASE for papers comparing CTCA and coronary angiography in TAVI candidates. The primary endpoint was the diagnostic accuracy of CTCA, compared to coronary angiography, for detection of significant (>50% diameter stenosis) coronary artery disease, measured as sensitivity, specificity, positive—(PPV) and negative predictive value (NPV). Seven studies were included, with a cumulative sample size of 1,275 patients. The patient-based pooled sensitivity, specificity, PPV and NPV were 95, 65, 71 and 94% respectively. Quality assessment revealed excellent and good quality in terms of applicability and risk of bias respectively, with the main concern being patient selection. In conclusion, on the basis of a significance cut-off value of 50% diameter stenosis, CTCA provides acceptable diagnostic accuracy for the exclusion of coronary artery disease in patients referred for TAVI. Using the routinely performed preoperative computed tomography scans as a gatekeeper for coronary angiography could decrease additional coronary angiographies by 37% in this high-risk and fragile population.

Cite

CITATION STYLE

APA

van den Boogert, T. P. W., Vendrik, J., Claessen, B. E. P. M., Baan, J., Beijk, M. A., Limpens, J., … Henriques, J. P. (2018). CTCA for detection of significant coronary artery disease in routine TAVI work-up. Netherlands Heart Journal, 26(12), 591–599. https://doi.org/10.1007/s12471-018-1149-6

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free