Arterial Stiffness and Coronary Ischemia: New Aspects and Paradigms
Purpose of Review
Aortic stiffness (AS) is widely associated with hypertension and considered as a major predictor of coronary heart disease (CHD). AS is measured using carotid–femoral pulse wave velocity (PWV), particularly when this parameter is associated with an index involving age, gender, heart rate, and mean blood pressure. The present review focuses on the interest of measurement of PWV and the calculation of individual PWV index for the prediction of CHD, in addition with the use of new statistical nonlinear models enabling results with very high levels of accuracy.
PWV index may so constitute a substantial marker of large arteries prediction and damage in CHD and may be also used in cerebrovascular and renal circulations models. PWV index determinations are particularly relevant to consider in angiographic CHD decisions and in the presence of vulnerable plaques with high cardiovascular risk. Due to the variability in symptoms and clinical characteristics of patients, together with some imperfections in results, there is no very simple adequate diagnosis approach enabling to improve the so defined CHD prediction in usual clinical practice.
In recent works in relation to “artificial intelligence” and involving “decision tree” models and “artificial neural networks,” it has been possible to determine consistent pathways introducing predictive medicine and enabling to obtain efficient algorithm classification models of coronary prediction.
KeywordsCoronary heart disease Artificial intelligence Data mining Pulse wave velocity Aortic stiffness Personalized medicine
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
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