Novel Non-invasive P Wave Analysis for the Prediction of Paroxysmal Atrial Fibrillation Recurrences in Patients Without Structural Heart Disease: a Prospective Pilot Study

Objectives: The pathogenetic mechanisms responsible for the initiation and recurrence of PAF are not fully elucidated and vary among individuals. We evaluated the ability of a novel non-invasive approach based on P wave wavelet analysis to predict symptomatic paroxysmal atrial fibrillation (PAF) recurrences in individuals without structural heart disease.

Methods: We studied 50 patients (24 males, mean age 54.9 ± 9.8 years) presented to our emergency department with a symptomatic episode of PAF. The patients were followed-up for 12.1 ± 0.1 months and classified into two groups according to the number of PAF episodes: Group A (<5 PAF, n = 33), Group B (≥ 5 PAF, n = 17). A third Group of 50 healthy individuals without history of PAF was used as control. Study groups underwent echocardiography and orthogonal ECG-based wavelet analyses of P waves at baseline and follow-up. Maximum and mean P wave energies were calculated in each subject at each orthogonal lead using the Morlet wavelet analysis.

Results: Larger P wave energies at X lead and relatively larger left atrium were independently associated with >5 PAF episodes vs. <5 PAF episodes. No difference in P wave duration was detected between Groups A and B (p > 0.1), whereas Group A and B patients had longer P waves at Z lead compared to Group C (86.4 ± 13 vs. 71.5 ± 15 msec, p < 0.001).

Conclusions: P wave wavelet analysis can reliably predict the generation and recurrence of PAF within a year. P wave wavelet analysis could contribute to the early identification of patients at risk for increased number of PAF recurrences.