ABSTRACT
Background
Traditional clinical parameters have not consistently predicted atrial fibrillation (AF) ablation outcomes in part because they are not measures of pathophysiologic mechanisms of disease and underlying substrate. Leaving Electrographic Flow (EGF)-identified extra-pulmonary vein (PV) sources unablated has been shown to result in more AF recurrence. Electrographic Flow Consistency (EGFC) measures the stability of flow vectors over space and time during AF and has been shown to correlate with high-density bipolar voltage mapping. Lower EGFC indicates more disorganized flow patterns characteristic of abnormal myocardial substrate and correlates with lower bipolar voltages.
Objective
Compare clinical parameters v. EGFC for predicting ablation outcomes.
Methods
Paroxysmal, persistent, and long-standing persistent AF patients prospectively underwent PV isolation (PVI)-only treatment followed by biatrial EGF mapping. Demographic/clinical variables were assessed during screening while EGFC and source presence were determined during intracardiac mapping. Freedom from AF (FFAF) was determined at 1-year post-procedure. Logistic regression models determined optimal cutoffs for FFAF prediction.
Results
A total of 88 patients with mean age 65±10 years, 31% female, and mean left atrial (LA) size 4.5±0.6 cm were analyzed. Age, LA size, left ventricular ejection fraction (LVEF), CHA2DS2-VASc and its individual components, AF duration, AF guidelines classification, atrial flutter history, number of prior ablation procedures were compared to EGFC and source presence. Of all variables analyzed, EGFC was correlated only to flutter history (r=0.45, p<0.001) and weakly to LA size (r=-0.33, p=0.002) and diabetes (r=-0.31, p=0.003), while source presence was only weakly correlated to age (r=0.35, p<0.001). EGFC and source presence were also stronger at separating patients by recurrence rates than any pair of clinical metrics and was also better than all clinical variables combined. Patients with EGFC>0.60 and no sources had 91% FFAF v. 22% in those with EGFC<0.60 and sources (p<0.001). By contrast, the best two clinical metrics at predicting FFAF were age <60.5 years and LA size <4.05 cm, but patients with both factors had 63% FFAF v. 37% with neither (p=0.124).
Conclusions
EGF metrics more strongly correlate with post-ablation FFAF than clinical parameters. Underlying AF pathophysiology may therefore be better reflected by EGFC and extra-PV source presence than general clinical variables like age, LA size, and LVEF.
