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http://dx.doi.org/10.1016/j.hrthm.2005.03.006 | DOI Listing |
Circulation
January 2025
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN (Y.N.V.R., A.T., M.M.R., B.A.B.).
Background: Plasma NT-proBNP (N-terminal pro-B-type natriuretic peptide) is commonly used to diagnose heart failure with preserved ejection fraction (HFpEF), but its diagnostic performance in the ambulatory/outpatient setting is unknown because previous studies lacked objective reference standards.
Methods: Among patients with chronic dyspnea, diagnosis of HFpEF or noncardiac dyspnea was determined conclusively by exercise catheterization in a derivation cohort (n=414), multicenter validation cohort 1 (n=560), validation cohort 2 (n=207), and a nonobese Japanese validation cohort 3 (n=77). Optimal NT-proBNP cut points for HFpEF rule out (optimizing sensitivity) and rule in (optimizing specificity) were derived and tested, stratified by obesity and atrial fibrillation.
Digit Health
January 2025
Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Objective: Although the evaluation of left ventricular ejection fraction (LVEF) in patients with atrial fibrillation (AF) or atrial flutter (AFL) is crucial for appropriate medical management, the prediction of reduced LVEF (<50%) with AF/AFL electrocardiograms (ECGs) lacks evidence. This study aimed to investigate deep-learning approaches to predict reduced LVEF (<50%) in patients with AF/AFL ECGs and easily obtainable clinical information.
Methods: Patients with 12-lead ECGs of AF/AFL and echocardiography were divided into those with LVEF <50% and ≥50%.
Heliyon
January 2025
Department of Information Engineering, Università Politecnica delle Marche, via Brecce Bianche, Ancona, 60131, Italy.
Background: Deep-learning applications in cardiology typically perform trivial binary classification and are able to discriminate between subjects affected or not affected by a specific cardiac disease. However, this working scenario is very different from the real one, where clinicians are required to recognize the occurrence of one cardiac disease among the several possible ones, performing a multiclass classification. The present work aims to create a new interpretable deep-learning tool able to perform a multiclass classification and, thus, discriminate among several different cardiac diseases.
View Article and Find Full Text PDFEuropace
December 2024
Research Group Cardiovascular Diseases, University of Antwerp, Prinsstraat 13, Antwerp 2000, Belgium.
Aims: Trials on integrated care for atrial fibrillation (AF) showed mixed results in different AF populations using various approaches. The multicentre, randomized AF-EduCare trial evaluated the effect of targeted patient education on unplanned cardiovascular outcomes.
Methods And Results: Patients willing to participate were randomly assigned to in-person education, online education, or standard care (SC) and followed for minimum 18 months.
Curr Probl Cardiol
January 2025
Department of Cardiology, Lanzhou University Second Hospital, Lanzhou, China. Electronic address:
Atrial fibrillation (AF) is tightly linked to mitochondrial dysfunction, calcium (Ca²⁺) imbalance, and oxidative stress. Mitochondrial Ca²⁺ is essential for regulating metabolic enzymes, maintaining the tricarboxylic acid (TCA) cycle, supporting the electron transport chain (ETC), and producing ATP. Additionally, Ca²⁺ modulates oxidative balance by regulating antioxidant enzymes and reactive oxygen species (ROS) clearance.
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