Characteristics of high-risk coronary plaques identified by computed tomographic angiography and associated prognosis: a systematic review and meta-analysis
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Open Access
- 20 December 2015
- journal article
- research article
- Published by Oxford University Press (OUP) in European Heart Journal – Cardiovascular Imaging
- Vol. 17 (2), 120-129
- https://doi.org/10.1093/ehjci/jev325
Abstract
To clarify the potential role of coronary computed tomographic angiography (CCTA) in characterizing and prognosticating high-risk coronary plaques. A systematic review and meta-analysis were conducted to compare high-risk vs. low-risk plaques and culprit vs. non-culprit lesions in patients with acute coronary syndrome (ACS) vs. stable angina (SA). High-risk plaques were defined by at least one of the following features: non-calcified plaque (NCP), the presence of spotty calcified plaque (SCP), or increased remodelling index (RI). Results of included studies were pooled as odds ratios (OR) or weighted mean differences (WMD) with 95% confidence interval (CI). Eighteen eligible studies provided data to compare plaque types, plaque volume, and RI. Six studies provided data on ACS events in vulnerable high-risk vs. low-risk calcified plaques after 35 ± 2 months of follow-up. ACS patients had significantly higher number of NCP and SCP compared with SA patients with OR = 1.96 (1.47–2.60; 95% CI) P = 0.0001 and OR = 4.5 (2.98–6.83; 95% CI) P = 0.0001, respectively. Total plaque volume in ACS was not larger than SA: WMD = 22.9 (−22.1 to 67; 95% CI) mm 3 , P = 0.32, but NCP volume was significantly larger: WMD = 28.8 (10.9–46.7; 95% CI) mm 3 , P = 0.002. RI was higher in culprit lesions in ACS compared with SA and compared with non-culprit lesions in ACS patients: WMD = 0.48 (0.25–0.70; 95% CI) P = 0.0001 and 0.19 (0.07–0.30) P = 0.0001, respectively. The associated risk of future ACS was significantly higher in high-risk than in low-risk plaques: OR = 12.1 (5.24–28.1; 95% CI) P = 0.0001. CCTA can non-invasively characterize high-risk vulnerable coronary plaques and can predict future ACS events in patients with high-risk plaques.This publication has 35 references indexed in Scilit:
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