Deep hypothermia has been the standard for hypothermic circulatory arrest (HCA) during aortic arch surgery. However, centers worldwide have shifted toward lesser hypothermia with antegrade cerebral perfusion. This has been supported by retrospective data, but there has yet to be a multicenter, prospective randomized study comparing deep versus moderate hypothermia during HCA.

Endothelial cell (EC) generation and turnover by self-proliferation contributes to vascular repair and regeneration. The ability to accurately measure the dynamics of EC generation would advance our understanding of cellular mechanisms of vascular homeostasis and diseases. However, it is currently challenging to evaluate the dynamics of EC generation in large vessels such as arteries because of their infrequent proliferation.

In addition to the traditional clinical risk factors, an increasing amount of imaging biomarkers have shown value for cardiovascular risk prediction. Clinical and imaging data are captured from a variety of data sources during multiple patient encounters and are often analyzed independently. Initial studies showed that fusion of both clinical and imaging features results in superior prognostic performance compared with traditional scores. There are different approaches to fusion modeling, combining multiple data resources to optimize predictions, each with its own advantages and disadvantages. However, manual extraction of clinical and imaging data is time and labor intensive and often not feasible in clinical practice. An automated approach for clinical and imaging data extraction is highly desirable. Convolutional neural networks and natural language processing can be utilized for the extraction of electronic medical record data, imaging studies, and free-text data. This review outlines the current status of cardiovascular risk prediction and fusion modeling; and in addition gives an overview of different artificial intelligence approaches to automatically extract data from images and electronic medical records for this purpose.

The neighborhoods where individuals reside shape environmental exposures, access to resources, and opportunities. The inequitable distribution of resources and opportunities across neighborhoods perpetuates and exacerbates cardiovascular health inequities. Thus, interventions that address the neighborhood environment could reduce the inequitable burden of cardiovascular disease in disenfranchised populations. The objective of this scientific statement is to provide a roadmap illustrating how current knowledge regarding the effects of neighborhoods on cardiovascular disease can be used to develop and implement effective interventions to improve cardiovascular health at the population, health system, community, and individual levels. PubMed/Medline, CINAHL, Cochrane Library reviews, and ClinicalTrials.gov were used to identify observational studies and interventions examining or targeting neighborhood conditions in relation to cardiovascular health. The scientific statement summarizes how neighborhoods have been incorporated into the actions of health care systems, interventions in community settings, and policies and interventions that involve modifying the neighborhood environment. This scientific statement presents promising findings that can be expanded and implemented more broadly and identifies methodological challenges in designing studies to evaluate important neighborhood-related policies and interventions. Last, this scientific statement offers recommendations for areas that merit further research to promote a deeper understanding of the contributions of neighborhoods to cardiovascular health and health inequities and to stimulate the development of more effective interventions.

Sodium-glucose cotransporter 2 inhibitors reduce the risk of worsening heart failure (HF) and cardiovascular death in patients with HF irrespective of left ventricular ejection fraction. It is important to determine whether therapies for HF improve symptoms and functional capacity.

Few clinical data are available on NEXN mutation carriers, and the gene's involvement in cardiomyopathies or sudden death has not been fully established. Our objectives were to assess the prevalence of putative pathogenic variants in NEXN and to describe the phenotype and prognosis of patients carrying the variants.

Resistance training not only can improve or maintain muscle mass and strength, but also has favorable physiological and clinical effects on cardiovascular disease and risk factors. This scientific statement is an update of the previous (2007) American Heart Association scientific statement regarding resistance training and cardiovascular disease. Since 2007, accumulating evidence suggests resistance training is a safe and effective approach for improving cardiovascular health in adults with and without cardiovascular disease. This scientific statement summarizes the benefits of resistance training alone or in combination with aerobic training for improving traditional and nontraditional cardiovascular disease risk factors. We also address the utility of resistance training for promoting cardiovascular health in varied healthy and clinical populations. Because less than one-third of US adults report participating in the recommended 2 days per week of resistance training activities, this scientific statement provides practical strategies for the promotion and prescription of resistance training.

Stress perfusion cardiovascular magnetic resonance can be performed without rest perfusion for the quantification of ischemia burden. However, the optimal method of analysis is uncertain.

The development of thoracic aortic calcium (TAC) temporally precedes coronary artery calcium more often in women versus men. Whether TAC density and area confer sex-specific differences in atherosclerotic cardiovascular disease (ASCVD) risk is unknown.

Overall outcomes and the escalation rate for home hospital admissions for heart failure (HF) are not known. We report overall outcomes, predict escalation, and describe care provided after escalation among patients admitted to home hospital for HF.