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Measurement of Pulse Propagation Velocity, Distensibility and Strain in an Abdominal Aortic Aneurysm Mouse Model
Published on: February 23, 2020
Aortic propagation velocity in predicting coronary artery disease: A systematic review and meta-analysis
Fereshteh Ghaderi1, Shabnam Niroomand2, Hoorak Poorzand1
1Cardiovascular Department, Echocardiography Laboratory, Faculty of Medicine, Mashhad University of Medical Science, Mashhad, Iran.
Insights
Aortic propagation velocity (APV) is a novel echocardiographic index that can predict coronary artery disease (CAD). This meta-analysis found APV has suitable sensitivity and specificity for screening CAD.
Area of Science:
- Cardiovascular Medicine
- Diagnostic Imaging
Background:
- Coronary artery disease (CAD) remains a leading cause of mortality and morbidity.
- Aortic propagation velocity (APV) is a novel echocardiographic index for CAD risk stratification.
Approach:
- A meta-analysis was conducted by systematically searching major electronic databases.
- Five studies involving 490 patients were included to evaluate the predictive role of APV in CAD.
- Comprehensive Meta-analysis 2.0 software was utilized for data synthesis.
Key Points:
- Pooled findings revealed significantly higher APV in the non-CAD group compared to the CAD group (SMD: 2.39).
- APV demonstrated a diagnostic sensitivity of 86.3% and specificity of 83.8% for predicting CAD.
- Significant differences in aortic distensibility and strain were observed between CAD and non-CAD patients.
Conclusions:
- APV shows predictive value for CAD with appropriate sensitivity and specificity.
- Aortic propagation velocity can serve as a valuable noninvasive tool for CAD screening.
Introduction:
Coronary artery disease (CAD) and its outcome, myocardial infarction, is yet a significant etiology of mortality and morbidity nowadays. The aortic propagation velocity (APV) can be a simple, straightforward and novel echocardiographic index for the risk stratification in the evaluation of CAD. In this meta-analysis, we evaluated the predictive role of APV in CAD.
Material And Methods:
Relevant electronic bibliographies (PubMed, ScienceDirect, Scopus, EMbase, the Cochrane library) were explored. Related reports were selected according to the inclusion and exclusion criteria. Meta-analysis was performed using the Comprehensive Meta-analysis 2.0 software.
Results:
Eventually, 5 articles met the inclusion criteria and included in the meta-analysis. Five studies with 490 patients reported the APV mean in CAD and non-CAD groups. A random-effect model was used and the pooled findings demonstrated a significant higher APV in non-CAD group compared to CAD group (SMD: 2.39, 95% CI: 1.70-3.07, P < .001, I2: 84%, Q: 19.03). The diagnostic value of APV in predicting CAD showed 86.3% sensitivity (95% CI: 74-91, P value < .001, I2: 65%, Q: 8.53, P value: .03) and 83.8% specificity (95% CI: 69-94, P value < .001, I2: 60%, Q: 9.89, P value: .01).
Conclusion:
There was a predictive role of APV in CAD with suitable specificity and sensitivity. Moreover, aortic distensibility and aortic strain were significantly different in CAD and non-CAD patients. APV could be used as a good noninvasive tool for screening CAD.
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