Back to Search Start Over

Classification of Left Atrial Diseased Tissue Burden Determined by Automated Voltage Analysis Predicts Outcomes after Ablation for Atrial Fibrillation

Authors :
Claire Howard
Szilvia Herczeg
László Gellér
Edward Keelan
Joseph Galvin
Katie Walsh
Gábor Széplaki
J Keaney
Source :
Disease Markers, Vol 2021 (2021), Disease Markers
Publication Year :
2021
Publisher :
Hindawi Limited, 2021.

Abstract

Background. The burden and persistence of atrial fibrillation (AF) have been associated with the presence and extent of left atrial (LA) fibrosis. Recent reports have implicated an association between the extent of LA fibrosis and the outcome of pulmonary vein isolation (PVI). We aimed to analyse the value of an automated scar quantification method in the prediction of success following PVI. Methods. One hundred and nine consecutive patients undergoing PVI for paroxysmal or persistent AF were included in our observational study with a 2-year follow-up. Prior to PVI, patients underwent high-definition LA electroanatomical mapping, and scar burden was quantified by automated software (Voltage Histogram Analysis, CARTO 3, Biosense Webster), then classified into 4 subgroups (Dublin Classes I-IV). Recurrence rates were analysed on and off antiarrhythmic drug therapy (AAD), respectively. Results. The overall success rate was 74% and 67% off AAD at 1- and 2-year follow-up, respectively. Patients with Dublin Class IV had significantly lower success rates ( p = 0.008 , off AAD). Dublin Class IV ( OR = 2.27 , p = 0.022 , off AAD) and the presence of arrhythmia in the blanking period ( OR = 3.28 , p = 0.001 , off AAD) were the only significant predictors of recurrence. The use of AAD did not affect these results. Conclusions. 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

Details

Language :
English
ISSN :
18758630 and 02780240
Volume :
2021
Database :
OpenAIRE
Journal :
Disease Markers
Accession number :
edsair.doi.dedup.....06755ba2a309c9dc101f27b01b68bcd5