JOURNAL ARTICLE

Clinical predictors of challenging atrioventricular node ablation procedure for rate control in patients with atrial fibrillation

Baptiste Polin, Nathalie Behar, Vincent Galand, Vincent Auffret, Albin Behaghel, Dominique Pavin, Jean-Claude Daubert, Philippe Mabo, Christophe Leclercq, Raphael P Martins
International Journal of Cardiology 2017 October 15, 245: 168-173
28874289

INTRODUCTION: Atrioventricular node (AVN) ablation is usually a simple procedure but may sometimes be challenging. We aimed at identifying pre-procedural clinical predictors of challenging AVN ablation.

METHODS: Patients referred for AVN ablation from 2009 to 2015 were retrospectively included. Baseline clinical data, procedural variables and outcomes of AVN ablation were collected. A "challenging procedure" was defined 1) total radiofrequency delivery to get persistent AVN block≥400s, 2) need for left-sided arterial approach or 3) failure to obtain AVN ablation.

RESULTS: 200 patients were included (71±10years). A total of 37 (18.5%) patients had "challenging" procedures (including 9 failures, 4.5%), while 163 (81.5%) had "non-challenging" ablations. In multivariable analysis, male sex (Odds ratio (OR)=4.66, 95% confidence interval (CI): 1.74-12.46), body mass index (BMI, OR=1.08 per 1kg/m2 , 95%CI 1.01-1.16), operator experience (OR=0.40, 95%CI 0.17-0.94), and moderate-to-severe tricuspid regurgitation (TR, OR=3.65, 95%CI 1.63-8.15) were significant predictors of "challenging" ablations. The proportion as a function of number of predictors was analyzed (from 0 to 4, including male sex, operator inexperience, a BMI>23.5kg/m2 and moderate-to-severe TR). There was a gradual increase in the risk of "challenging" procedure with the number of predictors by patient (No predictor: 0%; 1 predictor: 6.3%; 2 predictors: 16.5%; 3 predictors: 32.5%; 4 predictors: 77.8%).

CONCLUSIONS: Operator experience, male sex, higher BMI and the degree of TR were independent predictors of "challenging" AVN ablation procedure. The risk increases with the number of predictors by patient.

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