The aim of this article is to review sex differences in aortic stenosis (AS) assessed with multimodality imaging. Echocardiography remains the mainstay imaging technique to diagnose AS and provides important insights into the differences between men and women in relation to valve haemodynamic and left-ventricular response. However, echocardiography does not have adequate resolution to provide important insights into sex differences in the degenerative, calcific pathophysiological process of the aortic valve. CT shows that women with AS have more fibrotic changes of the aortic valve whereas men show more calcific deposits. Cardiac magnetic resonance shows that women have left ventricles that are less hypertrophic and smaller compared with those of men, while men have more replacement myocardial fibrosis. These differences may lead to different responses to aortic valve replacement because myocardial diffuse fibrosis but not replacement myocardial fibrosis may regress after the procedure. Sex differences in the pathophysiological process of AS can be assessed using multimodality imaging, assisting in decisionmaking in these patients.
In the past few decades, the accelerated improvement in technology has allowed the development of new and effective coronary and structural heart disease interventions. There has been inequitable patient access to these advanced therapies and significant disparities have affected patients from low socioeconomic positions. In the US, these disparities mostly affect women, black and hispanic communities who are overrepresented in low socioeconomic. Other adverse social determinants of health influenced by structural racism have also contributed to these disparities. In this article, we review the literature on disparities in access and use of coronary and structural interventions; delineate the possible reasons underlying these disparities; and highlight potential solutions at the government, healthcare system, community and individual levels.
It has been reported at the 2022 European Society of Cardiology Congress that the DELIVER trial has met its primary outcome - a relative reduction of 18% in a composite of worsening heart failure (HF) or cardiovascular death. These results, added to evidence from previously reported pivotal trials with sodium-glucose cotransporter-2 inhibitors (SGLT2is) in patients with reduced and preserved heart failure (HF), provide compelling evidence of the benefit of SGLT2is across the HF spectrum, irrespective of ejection fraction. New diagnostic algorithms that are quick and easy to implement at the point of care are needed for quick diagnosis and implementation of these drugs. Ejection fraction may come later for proper phenotyping.
Artificial intelligence (AI) is a broad term referring to any automated systems that need 'intelligence' to carry out specific tasks. During the last decade, AI-based techniques have been gaining popularity in a vast range of biomedical fields, including the cardiovascular setting. Indeed, the dissemination of cardiovascular risk factors and the better prognosis of patients experiencing cardiovascular events resulted in an increase in the prevalence of cardiovascular disease (CVD), eliciting the need for precise identification of patients at increased risk for development and progression of CVD. AI-based predictive models may overcome some of the limitations that hinder the performance of classic regression models. Nonetheless, the successful application of AI in this field requires knowledge of the potential pitfalls of the AI techniques, to guarantee their safe and effective use in daily clinical practice. The aim of the present review is to summarise the pros and cons of different AI methods and their potential application in the cardiovascular field, with a focus on the development of predictive models and risk assessment tools.
New evidence for acute coronary syndrome has been presented in Hot Line sessions at the 2022 European Society of Cardiology Congress in Barcelona. This editorial describes some of the highlights.