Abstract

Abstract Funding Acknowledgements Type of funding sources: None. BACKROUND Left atrium (LA) fibrosis has been shown to be an important factor associated with atrial fibrillation recurrence after catheter ablation (CA). Morphological features of the P wave have been related to the extent of atrial fibrosis as identified with electroanatomic mapping (EAM) in patients with paroxysmal atrial fibrillation (PAF) undergoing catheter ablation (CA). The ability to assess, by means of non-invasive markers, the electroanatomical substrate of the LA and the likelihood of PAF recurrence after CA, could be very useful in PAF management, patient selection for CA and improving outcomes. Purpose In the current prospective cohort study we aimed at establishing a pathophysiological basis of beat-to-beat (B2B) P-wave morphological and wavelet analysis, showing that it is associated with areas of considerable fibrosis, as identified with EAM in patients with PAF. Methods 44 patients with symptomatic paroxysmal AF, diagnosed at least 6 months before, were enrolled. 12-lead electrocardiogram (ECG) recordings, as well as 12 min vectorcardiogram (VCG) recordings were obtained from all patients, while EAM of left atrium (LA) was performed in all patients before radiofrequency CA. B2B P-wave morphological and wavelet analysis was performed according to a methodology described in previous publications. Results The 35 patients who were valid for statistical analysis were divided into 2 groups: in Group A the total low-voltage (<0.5 mV in EAM) area was greater than the median value of 5.55% (large low-voltage area), while in Group B the total low-voltage area was <5.55% (small low-voltage area). From the correlation between standard P-wave indices derived from 12-lead ECG and low-voltage areas only P-wave duration was significantly different between the two groups. From orthogonal ECG parameters analysis X axis was the most representative of low-voltage areas. B2B P-wave analysis revealed 3 features which showed a statistically significant difference between the 2 groups and no collinearity (Table 1). Logistic regression analysis of the non correlated variables for the prediction of low-voltage areas is shown in Table 2. It seems that a longer distance between the P-wave peak and the P-wave end, as well as a more «flattened» P-wave (small area with long duration) is associated with larger low-voltage areas and consequently more extensive LA fibrosis. Conclusions In patients with PAF and no overt atrial myopathy, B2B wavelet analysis may be a useful non-invasive tool for the prediction of low-voltage areas, representing fibrosis in the LA. Further studies in larger cohorts of patients are needed in order to confirm these findings and enable the use of B2B wavelet analysis in clinical practice.

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