Publications by authors named "Elena Cozza"

Coronary artery disease (CAD) is the leading global cause of mortality, accounting for approximately 30% of all deaths. It is primarily characterized by the accumulation of atherosclerotic plaques within the coronary arteries, leading to reduced blood flow to the heart muscle. Early detection of atherosclerotic plaques is crucial to prevent major adverse cardiac events.

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Article Synopsis
  • - The study investigates the use of cardiac computed tomography angiography (CCTA) as a non-invasive alternative to invasive coronary angiography (ICA) for assessing cardiac allograft vasculopathy (CAV) after heart transplantation.
  • - Conducted from March 2021 to February 2023, the research included 260 heart transplant patients, revealing that those undergoing CCTA had significantly lower costs and shorter hospital stays compared to those who underwent ICA.
  • - The findings suggest that CCTA is a safer and more cost-effective option for CAV surveillance post-heart transplantation, using less contrast and radiation than ICA.
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Article Synopsis
  • Heart transplantation is a key treatment for severe heart failure, improving both survival and quality of life for patients, but requires ongoing monitoring for best results.
  • Current guidelines on monitoring methods are not detailed, especially regarding the use of echocardiograms and cardiac magnetic resonance as alternatives to invasive procedures like endomyocardial biopsies.
  • Recent advancements in non-invasive imaging techniques, such as advanced echocardiography and cardiac computed tomography, show potential for reducing invasive procedures while still providing valuable insights into heart health post-transplant.
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Article Synopsis
  • - Cardiac computed tomography angiography (CCTA) is an effective and efficient method for identifying coronary artery disease, with the coronary artery calcium (CAC) score being a key measure for evaluating cardiovascular risk.
  • - The CAC score, particularly when analyzed alongside plaque characteristics, provides better risk assessment than traditional methods, especially for asymptomatic patients, indicating that a score of 0 suggests a favorable prognosis and higher scores signal increased cardiovascular risk.
  • - The paper discusses how integrating CAC scoring with machine learning could improve risk stratification and clinical decision-making for patients with cardiovascular concerns.
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