P-Wave Duration/Amplitude Ratio Quantifies Atrial Low-Voltage Area and Predicts Atrial Arrhythmia Recurrence After Pulmonary Vein Isolation.

Can J Cardiol

Division of Cardiology, Peter Munk Cardiac Centre, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada. Electronic address:

Published: October 2023

Background: Atrial low-voltage areas (LVAs) in patients with atrial fibrillation increase the risk of atrial arrhythmia (AA) recurrence after pulmonary vein isolation (PVI). Contemporary LVA prediction scores (DR-FLASH, APPLE) do not include P-wave metrics. We aimed to evaluate the utility of P-wave duration/amplitude ratio (PWR) in quantifying LVA and predicting AA recurrence after PVI.

Methods: In 65 patients undergoing first-time PVI, 12-lead ECGs were recorded during sinus rhythm. PWR was calculated as the ratio between the longest P-wave duration and P-wave amplitude in lead I. High-resolution biatrial voltage maps were collected and LVAs included bipolar electrogram amplitudes < 0.5 mV or < 1.0 mV. An LVA quantification model was created with the use of clinical variables and PWR, and then validated in a separate cohort of 24 patients. Seventy-eight patients were followed for 12 months to evaluate AA recurrence.

Results: PWR strongly correlated with left atrial (LA) (< 0.5 mV: r = 0.60; < 1.0 mV: r = 0.68; P < 0.001) and biatrial LVA (< 0.5 mV: r = 0.63; < 1.0 mV: r = 0.70; P < 0.001). Addition of PWR to clinical variables improved model quantification of LA LVA at the < 0.5 mV (adjusted R = 0.59 to 0.68) and < 1.0 mV (adjusted R = 0.59 to 0.74) cutoffs. In the validation cohort, PWR model-predicted LVA correlated strongly with measured LVA (< 0.5 mV: r = 0.78; < 1.0 mV: r = 0.81; P < 0.001). PWR model was superior to DR-FLASH (area under the receiver operating characteristic curve [AUC] 0.90 vs 0.78; P = 0.030) and APPLE (AUC 0.90 vs 0.67; P = 0.003) at detecting LA LVA and similar at predicting AA recurrence after PVI (AUC 0.67 vs 0.65 and 0.60).

Conclusion: Our novel PWR model accurately quantifies LVA and predicts AA recurrence after PVI. PWR model-predicted LVA may help guide patient selection for PVI.

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http://dx.doi.org/10.1016/j.cjca.2023.04.014DOI Listing

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