Quantification of Myocardial Contraction Fraction with Three-Dimensional Automated, Machine-Learning-Based Left-Heart-Chamber Metrics: Diagnostic Utility in Hypertrophic Phenotypes and Normal Ejection Fraction.

The differentiation of left ventricular (LV) hypertrophic phenotypes is challenging in patients with normal ejection fraction (EF). The myocardial contraction fraction (MCF) is a simple dimensionless index useful for specifically identifying cardiac amyloidosis (CA) and hypertrophic cardiomyopathy (HCM) when calculated by cardiac magnetic resonance. The purpose of this study was to evaluate the value of MCF measured by three-dimensional automated, machine-learning-based LV chamber metrics (dynamic heart model [DHM]) for the discrimination of different forms of hypertrophic phenotypes.

Atrial fibrillation in vascular surgery: a systematic review and meta-analysis on prevalence, incidence and outcome implications.

Aims: To know the prevalence of atrial fibrillation (AF), as well as the incidence of postoperative AF (POAF) in vascular surgery for arterial diseases and its outcome implications.

Methods: We performed a systematic review and meta-analysis following the PRISMA statement.

Results: After the selection process, we analyzed 44 records (30 for the prevalence of AF history and 14 for the incidence of POAF).

DIGItal Health Literacy after COVID-19 Outbreak among Frail and Non-Frail Cardiology Patients: The DIGI-COVID Study.

Background: Telemedicine requires either the use of digital tools or a minimum technological knowledge of the patients. Digital health literacy may influence the use of telemedicine in most patients, particularly those with frailty. We aimed to explore the association between frailty, the use of digital tools, and patients' digital health literacy.

Three-Dimensional Automated, Machine-Learning-Based Left Heart Chamber Metrics: Associations with Prevalent Vascular Risk Factors and Cardiovascular Diseases.

Background. Three-dimensional transthoracic echocardiography (3DE) powered by artificial intelligence provides accurate left chamber quantification in good accordance with cardiac magnetic resonance and has the potential to revolutionize our clinical practice. Aims.

Sustained right ventricular dysfunction in severe COVID-19: The role of disseminated intravascular coagulation.

Background: Acute right ventricular (RV) failure is common in patients hospitalized with COVID-19. Compared to the conventional echocardiographic parameters, right ventricular longitudinal strain (RVLS) is more sensitive and accurate for the diagnosis of RV systolic dysfunction.

Objective: Our purpose was to investigate the sustained RV dysfunction echo-quantified by RVLS in patients recovered from severe COVID-19.