title: Role of the P-wave high frequency energy and duration as noninvasive cardiovascular predictors of paroxysmal atrial fibrillation.
abstract: A normal cardiac activation starts in the sinoatrial node and then spreads throughout the atrial myocardium, thus defining the P-wave of the electrocardiogram. However, when the onset of paroxysmal atrial fibrillation (PAF) approximates, a highly disturbed electrical activity occurs within the atria, thus provoking fragmented and eventually longer P-waves. Although this altered atrial conduction has been successfully quantified just before PAF onset from the signal-averaged P-wave spectral analysis, its evolution during the hours preceding the arrhythmia has not been assessed yet. This work focuses on quantifying the P-wave spectral content variability over the 2h preceding PAF onset with the aim of anticipating as much as possible the arrhythmic episode envision. For that purpose, the time course of several metrics estimating absolute energy and ratios of high- to low-frequency power in different bands between 20 and 200Hz has been computed from the P-wave autoregressive spectral estimation. All the analyzed metrics showed an increasing variability trend as PAF onset approximated, providing the P-wave high-frequency energy (between 80 and 150Hz) a diagnostic accuracy around 80% to discern between healthy subjects, patients far from PAF and patients less than 1h close to a PAF episode. This discriminant power was similar to that provided by the most classical time-domain approach, i.e., the P-wave duration. Furthermore, the linear combination of both metrics improved the diagnostic accuracy up to 88.07%, thus constituting a reliable noninvasive harbinger of PAF onset with a reasonable anticipation. The information provided by this methodology could be very useful in clinical practice either to optimize the antiarrhythmic treatment in patients at high-risk of PAF onset and to limit drug administration in low risk patients.
authors.affiliation: Innovation in Bioengineering Research Group, University of Castilla-La Mancha, Spain.. Electronic address: raul.alcaraz@uclm.es.
authors.forename: Raúl
authors.initials: R
authors.lastname: Alcaraz
authors.affiliation: Innovation in Bioengineering Research Group, University of Castilla-La Mancha, Spain.
authors.forename: Arturo
authors.initials: A
authors.lastname: Martínez
authors.affiliation: Biomedical Synergy, Electronic Engineering Department, Universidad Politécnica de Valencia, Spain.
authors.forename: José J
authors.initials: JJ
authors.lastname: Rieta
mesh_terms: D000368:Aged; D001281:Atrial Fibrillation / Q000175:diagnosis* / Q000503:physiopathology; D016022:Case-Control Studies; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies
keywords: Atrial fibrillation; Autoregressive modeling; Electrocardiogram; Spectral analysis; Surface P-wave