Publications by authors named "D M Luria"
AI-based cluster analysis enables outcomes prediction among patients with increased LVM.
Front Cardiovasc Med
September 2024
Background: The traditional classification of left ventricular hypertrophy (LVH), which relies on left ventricular geometry, fails to correlate with outcomes among patients with increased LV mass (LVM).
Objectives: To identify unique clinical phenotypes of increased LVM patients using unsupervised cluster analysis, and to explore their association with clinical outcomes.
Methods: Among the UK Biobank participants, increased LVM was defined as LVM index ≥72 g/m for men, and LVM index ≥55 g/m for women.
Article Synopsis
- * Analyzed outcomes between patients who received imaging and those who did not, finding no significant differences in complications, recurrence of atrial fibrillation, or re-hospitalization rates after one year.
- * Despite longer procedure times for those who underwent imaging (90 minutes vs. 74.5 minutes), the study concludes that pre-procedural imaging does not impact the safety or efficacy of PVI in managing atrial fibrillation.
Sudden cardiac death (SCD) occurs unexpectedly and is usually a result of ventricular arrhythmia in patients with structural heart disease. The implantable cardioverter-defibrillator (ICD), with or without biventricular pacing, has been proven to be protective for heart failure patients with reduced ejection fraction of <35 % (HFrEF). This device therapy prevents SCD, with additional optimal medications, namely angiotensin-converting enzyme-inhibitors, angiotensin-II receptor-blockers, beta-blockers and mineralocorticoid receptor-antagonists.
View Article and Find Full Text PDFBackground: Atrial fibrillation (AF) is a common diagnosis in patients presenting to urgent care centers (UCCs), yet there is scant research regarding treatment in these centers. While some of these patients are managed within UCCs, some are referred for further care in an emergency department (ED).
Objectives: We aimed to identify the rate of patients referred to an ED and define predictors for this outcome.