4.6 Article

Predictors for Progression of Atrial Fibrillation in Patients Awaiting Atrial Fibrillation Ablation

Journal

CANADIAN JOURNAL OF CARDIOLOGY
Volume 32, Issue 11, Pages 1348-1354

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.cjca.2016.02.031

Keywords

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Funding

  1. German Cardiac Society (DGK)

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Background: Success rates of atrial fibrillation (AF) ablation have been shown to be significantly lower for patients with persistent AF. However, little is known about the risk factors predicting progression to persistent AF in patients awaiting AF ablation. Methods: We performed a retrospective, single-centre investigation of patients with paroxysmal AF at the time of placement on the ablation waiting list. Patients were defined as having progressed if they had developed self-reported or electrocardiogram-recorded AF durations more than 7 days while awaiting ablation. After ablation, clinical visits at 3, 6, 9, 12, and 18 months were performed with a minimum of a 48-hour-Holter and electrocardiogram. Baseline characteristics including left atrial diameter (LA) and the HATCH score were analyzed by univariable and multivariable analysis for predicting progression to persistent AF. Results: During a median waiting time of 9.7 (6.1, 14.2) months, 60 of 564 patients (11%) progressed to persistent AF. In patients who progressed, ablation took longer (180 [150, 249] minutes vs 157 [125, 210] minutes; P = 0.009) and was associated with a higher rate of recurrence after a median of 12 months (53.3% vs 39.1%; P < 0.001). The HATCH score was a poor predictor of AF progression (area under the curve 0.54), whereas an LA diameter of more than 45 mm (odds ratio 3.46, P < 0.001) and heart failure (odds ratio 3.11, P = 0.036) were strong and independent predictors of AF progression in multivariable analysis. Conclusions: Patients with an increased LA diameter or heart failure have a significantly increased risk of progression to persistent AF. These characteristics may define patients who should undergo earlier catheter ablation to optimize outcome.

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