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Atrial Remodeling

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Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while ...

Machine Learning Algorithm to Predict Atrial Fibrillation Using Serial 12-Lead ECGs Based on Left Atrial Remodeling.

Journal of the American Heart Association
BACKGROUND: We hypothesized that analysis of serial ECGs could predict new-onset atrial fibrillation (AF) more accurately than analysis of a single ECG by detecting the subtle cardiac remodeling that occurs immediately before AF occurrence. Our aim i...

Left Atrial Wall Thickness Measured by a Machine Learning Method Predicts AF Recurrence After Pulmonary Vein Isolation.

Journal of cardiovascular electrophysiology
BACKGROUND: Left atrial (LA) remodeling plays a significant role in the progression of atrial fibrillation (AF). Although LA wall thickness (LAWT) has emerged as an indicator of structural remodeling, its impact on AF outcomes remains unclear. We aim...

12 lead surface ECGs as a surrogate of atrial electrical remodeling - a deep learning based approach.

Journal of electrocardiology
BACKGROUND AND PURPOSE: Atrial fibrillation (AF), a common arrhythmia, is linked with atrial electrical and structural changes, notably low voltage areas (LVAs) which are associated with poor ablation outcomes and increased thromboembolic risk. This ...