Literature DB >> 27823601

Usefulness of P-Wave Duration and Morphologic Variability to Identify Patients Prone to Paroxysmal Atrial Fibrillation.

Giulio Conte1, Adrian Luca2, Sasan Yazdani2, Maria Luce Caputo3, François Regoli3, Tiziano Moccetti3, Lukas Kappenberger3, Jean-Marc Vesin2, Angelo Auricchio3.   

Abstract

Few data are available on the assessment of P-wave beat-to-beat morphology variability and its ability to identify patients prone to paroxysmal atrial fibrillation (AF) occurrence. Aim of this study was to determine whether electrocardiographic (ECG) parameters resulting from the beat-to-beat analysis of P wave in ECG recorded during sinus rhythm could be indicators of paroxysmal AF susceptibility. ECGs of 76 consecutive patients including 36 patients with history of AF and no overt structural cardiac abnormalities and a control group of 40 healthy patients without history of AF were analyzed. After preprocessing, features based on P waves and RR intervals were extracted from lead II of a 5-minute ECG recorded during sinus rhythm. The discriminative power of the extracted features was assessed. Among extracted features, the most discriminative ones to identify patients with paroxysmal episodes of AF were the mean P-wave duration and the SD of beat-to-beat Euclidean distance between P waves (an indicator of beat-to-beat P-wave morphologic variability). Patients with history of AF presented a significantly longer P-wave duration (125 ± 18 vs 110 ± 8 ms, p <0.001) and higher variability of P-wave morphology over time (beat-to-beat Euclidean distance: 0.11 ± 0.07 vs 0.076 ± 0.02, p <0.01) compared to patients without history of AF. Combination of P-wave duration and standard deviation of beat-to-beat Euclidean distance led to an accuracy of 88% in the discrimination between the 2 groups of patients. In conclusion, combination of P-wave duration and beat-to-beat Euclidean distance between P waves efficiently discriminates patients with history of AF and no overt structural cardiac abnormalities from healthy age-matched subjects, and it might be used as an effective tool to identify patients prone to paroxysmal AF occurrence.
Copyright © 2016 Elsevier Inc. All rights reserved.

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Year:  2016        PMID: 27823601     DOI: 10.1016/j.amjcard.2016.09.043

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  7 in total

1.  Signal-averaged P wave area increases during respiratory events in patients with paroxysmal atrial fibrillation and obstructive sleep apnea.

Authors:  Ken Monahan; Edward Hodges; Arpit Agrawal; Raghu Upender; Robert L Abraham
Journal:  Sleep Breath       Date:  2019-03-18       Impact factor: 2.816

2.  Predictive value of unshielded magnetocardiographic mapping to differentiate atrial fibrillation patients from healthy subjects.

Authors:  Gianluigi Guida; Anna Rita Sorbo; Riccardo Fenici; Donatella Brisinda
Journal:  Ann Noninvasive Electrocardiol       Date:  2018-06-27       Impact factor: 1.468

3.  Physiologic heart rate dependency of the PQ interval and its sex differences.

Authors:  Ondřej Toman; Katerina Hnatkova; Peter Smetana; Katharina M Huster; Martina Šišáková; Petra Barthel; Tomáš Novotný; Georg Schmidt; Marek Malik
Journal:  Sci Rep       Date:  2020-02-13       Impact factor: 4.379

4.  Short P-Wave Duration is a Marker of Higher Rate of Atrial Fibrillation Recurrences after Pulmonary Vein Isolation: New Insights into the Pathophysiological Mechanisms Through Computer Simulations.

Authors:  Angelo Auricchio; Tardu Özkartal; Francesca Salghetti; Laura Neumann; Simone Pezzuto; Ali Gharaviri; Andrea Demarchi; Maria Luce Caputo; François Regoli; Carlo De Asmundis; Gian-Battista Chierchia; Pedro Brugada; Catherine Klersy; Tiziano Moccetti; Ulrich Schotten; Giulio Conte
Journal:  J Am Heart Assoc       Date:  2021-01-07       Impact factor: 5.501

5.  Extended ECG Improves Classification of Paroxysmal and Persistent Atrial Fibrillation Based on P- and f-Waves.

Authors:  Matthias Daniel Zink; Rita Laureanti; Ben J M Hermans; Laurent Pison; Sander Verheule; Suzanne Philippens; Nikki Pluymaekers; Mindy Vroomen; Astrid Hermans; Arne van Hunnik; Harry J G M Crijns; Kevin Vernooy; Dominik Linz; Luca Mainardi; Angelo Auricchio; Stef Zeemering; Ulrich Schotten
Journal:  Front Physiol       Date:  2022-03-04       Impact factor: 4.566

6.  P-Wave Beat-to-Beat Analysis to Predict Atrial Fibrillation Recurrence after Catheter Ablation.

Authors:  Dimitrios Tachmatzidis; Anastasios Tsarouchas; Dimitrios Mouselimis; Dimitrios Filos; Antonios P Antoniadis; Dimitrios N Lysitsas; Nikolaos Mezilis; Antigoni Sakellaropoulou; Georgios Giannopoulos; Constantinos Bakogiannis; Konstantinos Triantafyllou; Nikolaos Fragakis; Konstantinos P Letsas; Dimitrios Asvestas; Michael Efremidis; Charalampos Lazaridis; Ioanna Chouvarda; Vassilios P Vassilikos
Journal:  Diagnostics (Basel)       Date:  2022-03-28

7.  Effects of occlusal disharmony on susceptibility to atrial fibrillation in mice.

Authors:  Kenji Suita; Yuka Yagisawa; Yoshiki Ohnuki; Daisuke Umeki; Megumi Nariyama; Aiko Ito; Yoshio Hayakawa; Ichiro Matsuo; Yasumasa Mototani; Yasutake Saeki; Satoshi Okumura
Journal:  Sci Rep       Date:  2020-08-13       Impact factor: 4.379

  7 in total

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