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Published on: September 8, 2023
Aorta unfolding index as an indicator for coronary artery disease severity
Amal Abdelsattar Sakrana1, Ahmed Abdel Khalek Abdel Razek1, Ahmed Ibrahim Bedier Abdelnaby2
1Department of Diagnostic and Interventional Radiology, 68780Mansoura University Hospital, Mansoura, Egypt.
Insights
The aortic unfolding index (AUI) predicts severe coronary artery disease (CAD) independent of age. AUI ≥66 showed high sensitivity and specificity for detecting significant stenosis in patients with CAD.
Area of Science:
- Cardiology
- Radiology
- Medical Imaging
Background:
- The aortic unfolding index (AUI) is a known predictor of cardiovascular events.
- Limited research exists on the association between AUI and coronary artery disease (CAD) severity.
Purpose of the Study:
- To determine the correlation between aortic unfolding and the severity of coronary artery disease.
- To evaluate AUI's potential as a biomarker for CAD severity.
Main Methods:
- Retrospective analysis of 115 patients with varying degrees of CAD.
- Correlation of AUI, derived from non-contrast CT, with the Gensini score.
- Assessment of AUI's sensitivity and specificity for detecting severe stenosis.
Main Results:
- Aortic unfolding index (AUI) significantly correlated with CAD severity and patient age.
- Multivariate analysis confirmed AUI as an independent predictor of severe CAD.
- An AUI cutoff of ≥66 demonstrated 94.9% sensitivity and 81.6% specificity for severe stenosis.
Conclusions:
- Aortic unfolding index (AUI) ≥66 is a significant predictor of severe coronary artery disease.
- This association is independent of patient age, highlighting AUI's specific predictive value.
Background:
Aortic unfolding index (AUI) is an independent predictor of cardiovascular events, yet there is scarcity in the literature on its association with the severity of coronary artery disease (CAD).
Purpose:
To investigate the correlation between aortic unfolding and coronary artery disease severity score.
Material And Methods:
The study included 115 patients with various degrees of CAD who underwent invasive coronary angiography and were retrospectively studied. AUI derived from non-contrast computed tomography (CT) of the chest was correlated to the Gensini score describing the CAD severity. Its sensitivity and specificity in the detection of severe stenosis were examined at various cutoff points.
Results:
CAD severity was significantly correlated with the patient age and AUI. On multivariate regression analysis, AUI was an independent predictor of severe CAD. The best cutoff value was ≥66, with 94.9% sensitivity and 81.6% specificity.
Conclusion:
AUI ≥66 was a predictor of severe CAD independent of the patient age.
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