Classification of Left Atrial Diseased Tissue Burden Determined by Automated Voltage Analysis Predicts Outcomes after Ablation for Atrial Fibrillation.
Szilvia HerczegJohn J KeaneyEdward KeelanClaire HowardKatie WalshLaszlo GellerGábor SzéplakiJoseph W GalvinPublished in: Disease markers (2021)
We propose a classification of low voltage areas based on automated quantification by software during 3D mapping prior to PVI. Patients with high burden of low voltage areas (>31% of <0.5 mV, Dublin Class IV) have a higher risk of recurrence following PVI. Information gathered during electroanatomical mapping may have important prognostic value.
Keyphrases
- left atrial
- deep learning
- atrial fibrillation
- catheter ablation
- machine learning
- mitral valve
- high resolution
- left ventricular
- high throughput
- left atrial appendage
- oral anticoagulants
- high density
- heart failure
- risk factors
- healthcare
- coronary artery disease
- mass spectrometry
- percutaneous coronary intervention
- venous thromboembolism
- data analysis
- free survival