Prognostic value of absence or presence of coronary artery disease determined by 64-slice computed tomography coronary angiography A systematic review ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2011-03

AUTHORS

Jawdat Abdulla, Camilla Asferg, Klaus Fuglsang Kofoed

ABSTRACT

To determine via a meta-analysis the prognostic value of 64-slice computed tomography angiography (CTA) by quantifying risk of major adverse cardiac events (MACE) in different patient groups classified according to CT angiographic findings. A systematic literature search and meta-analyses was conducted on 10 studies examining stable, symptomatic and intermediate risk patients by 64-slice CTA. Patients were followed up for a mean of 21 month. Patient groups with CT-angiographic non-obstructive (stenosis <50% of luminal narrowing) or obstructive (stenosis ≥50% of luminal narrowing) CAD were compared to those having normal angiography without CAD. MACE (cardiac death, non-fatal myocardial infarction and revascularization) numbers were used to calculate odds ratios (OR) with 95% confidence interval (CI) in each group. Ten studies including 5,675 patients were eligible for meta-analysis. The cumulative MACE rate over 21 months were 0.5% in patients with normal CTA, 3.5% in non-obstructive CAD and 16% in obstructive CAD. Compared to normal CTA, non-obstructive CAD was associated with significant increased risk of MACE with OR=6.68 (3.01-14.82 CI 95%), P=0.0001. Obstructive CAD was associated with further significant increased risk of MACE with OR=41.19 (22.56-75.18, CI 95%), P=0.0001. The studies were homogenous, P-value >0.05 for heterogeneity. 64-slice CTA is able to differentiate low-risk from high-risk patients with suspected or known CAD. Absence of CAD predicts excellent prognosis, while obstructive CAD is associated with markedly increased risk of MACE. More... »

PAGES

413-420

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10554-010-9652-x

DOI

http://dx.doi.org/10.1007/s10554-010-9652-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1033754689

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20549366


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