Ablation of atrial fibrillation is one of the most widely applied invasive procedures in cardiovascular medicine, and populations with atrial fibrillation continuously rise. Recurrence rates are, however, consistently high, even in patients without severe comorbidities. Robust stratification algorithms to distinguish patients suitable for ablation are generally lacking. This is a fact caused by the inability to incorporate evidence of atrial remodeling and fibrosis, e.g., atrial remodeling, in the decision pathways. Cardiac magnetic resonance is a powerful tool in identifying fibrosis; however, it is costly and not routinely used. Electrocardiography has been generally underutilized in clinical practice during pre-ablative screening. One of the characteristics of the electrocardiogram that can give us valuable data depicting the existence and the extent of atrial remodeling and fibrosis is the duration of the P-wave. Currently, many studies support the implementation of P-wave duration in the routine practice of patient evaluation as a surrogate marker of existing atrial remodeling, that in turn predicts recurrence after ablation of atrial fibrillation. Further research is guaranteed to establish this electrocardiographic characteristic in our stratification quiver.
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http://dx.doi.org/10.1016/j.hjc.2023.02.008 | DOI Listing |
BMC Cardiovasc Disord
January 2025
ITACA Institute, Universitat Politècnica de València, València, Spain.
Background: Complexity and signal recurrence metrics obtained from body surface potential mapping (BSPM) allow quantifying atrial fibrillation (AF) substrate complexity. This study aims to correlate electrocardiographic imaging (ECGI) detected reentrant patterns with BSPM-calculated signal complexity and recurrence metrics.
Methods: BSPM signals were recorded from 28 AF patients (17 male, 11 women, 62.
Nat Commun
January 2025
Interfakultäres Institut für Biochemie, University of Tübingen, Tübingen, Germany.
A balanced activity of cGMP signaling contributes to the maintenance of cardiovascular homeostasis. Vascular smooth muscle cells (VSMCs) can generate cGMP via three ligand-activated guanylyl cyclases, the NO-sensitive guanylyl cyclase, the atrial natriuretic peptide (ANP)-activated GC-A, and the C-type natriuretic peptide (CNP)-stimulated GC-B. Here, we study natriuretic peptide signaling in murine VSMCs and atherosclerotic lesions.
View Article and Find Full Text PDFHeart Rhythm
January 2025
Cardiology Department, Tulane University School of Medicine, New Orleans, Louisiana, United States. Electronic address:
Background: Causal machine learning (ML) provides an efficient way of identifying heterogeneous treatment effect groups from hundreds of possible combinations, especially for randomized trial data.
Objective: The aim of this paper is to illustrate the potential of applying causal ML on the DECAAF II trial data. We proposed a causal ML model to predict the treatment response heterogeneity.
Eur Heart J Cardiovasc Imaging
January 2025
Department of Cardiology, University of Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, Rennes, France.
Structural, architectural, contractile or electrophysiological alterations may occur in the left atrium (LA). The concept of LA cardiopathy is supported by accumulating scientific evidence demonstrating that LA remodeling has become a cornerstone diagnostic and prognostic marker. The structure and the function of LA and left atrial appendage (LAA) which is an integral part of the LA, are key elements for a better understanding of multiple clinical conditions, most notably atrial fibrillation (AF), cardioembolism, heart failure and mitral valve diseases.
View Article and Find Full Text PDFJ Prev Alzheimers Dis
January 2025
Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
Background: Atrial fibrillation (AF) has been associated with elevated dementia risk, while few studies have examined the role of the optimal glycemic status in disease trajectories of AF and dementia.
Objectives: We aim to evaluate associations between glycemic status with disease trajectories of AF and dementia, as well as major dementia subtypes, including Alzheimer's disease and vascular dementia.
Design: Population-based cohort study.
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