Pressure-based physiological evaluation of coronary artery disease is well established, but its application is limited in left main coronary artery (LMCA) disease. Our aim was to investigate whether pressure-based indices are comparable in the left anterior descending (LAD) and left circumflex artery (LCx) branches of the LMCA, and if discordance is due to differences in microvascular function in these territories.

The Get With the Guidelines-Heart Failure program was developed in 2005 with the goal of bringing evidence-based guidelines in heart failure management into widespread clinical practice. The program includes workshops, webinars, tool kits, chart abstraction, performance benchmarking, and achievement awards to drive quality improvement at participating hospitals. Two decades after its inception, the program has grown to include over 600 participating institutions across the United States. Linking registry data to Centers for Medicare and Medicaid Services claims has also allowed for the evaluation of longitudinal outcomes. Get With the Guidelines-Heart Failure has helped improve the quality of care for patients and has contributed substantially to the understanding of clinical science and optimal management of heart failure. This narrative review provides an overview of the indelible impact of the Get With the Guidelines-Heart Failure program on quality heart failure care over the past 20 years and highlights future challenges and directions.

Coronary stenting alters vessel dynamics, displacing hinge movement closer to stent edges. We aimed to investigate whether calcified nodules (CNs) are more frequent at stent edges associated with calcium.

The impact of lipid core burden index (LCBI) after percutaneous coronary intervention (PCI) in the stented segment assessed by intracoronary near-infrared spectroscopy on the outcomes remains unclear.

Aortic stenosis (AS) involves calcific and fibrotic degeneration of the valve tissue. The only noninvasive method for evaluating both processes is contrast-enhanced computed tomography angiography. We aimed to explore the differences in aortic valve (AV) tissue composition across sex, race/ethnicity, and AS hemodynamic phenotype in US patients referred for transcatheter AV replacement planning.

Despite advances in cardiovascular care and improved outcomes, fragmented healthcare systems, nonequitable access to health care, and nonuniform and unbiased collection and access to healthcare data have exacerbated disparities in healthcare provision and further delayed the technological-enabled implementation of precision medicine. Precision medicine relies on a foundation of accurate and valid omics and phenomics that can be harnessed at scale from electronic health records. Big data approaches in noncardiovascular healthcare domains have helped improve efficiency and expedite the development of novel therapeutics; therefore, applying such an approach to cardiovascular precision medicine is an opportunity to further advance the field. Several endeavors, including the American Heart Association Precision Medicine platform and public-private partnerships (such as BigData@Heart in Europe), as well as cloud-based platforms, such as Terra used for the National Institutes of Health All of Us, are attempting to temporally and ontologically harmonize data. This state-of-the-art review summarizes best practices used in cardiovascular genomic and precision medicine and provides recommendations for systems' requirements that could enhance and accelerate the integration of these platforms.

Heart failure (HF) is a highly prevalent condition characterized by exercise intolerance, an important metric for ambulatory prognostication. However, current methods to assess exercise capacity are often limited to tertiary HF centers, lacking scalability or accessibility. Wearable devices can enable near-continuous dynamic biometrics including exercise tolerance.

In hypertrophic cardiomyopathy (HCM), the mechanisms through which pathogenic sarcomere variants (G+) lead to left ventricular hypertrophy (LVH) are not understood.