Literature DB >> 24814497

Clinical classifications of atrial fibrillation poorly reflect its temporal persistence: insights from 1,195 patients continuously monitored with implantable devices.

Efstratios I Charitos1, Helmut Pürerfellner2, Taya V Glotzer3, Paul D Ziegler4.   

Abstract

OBJECTIVES: This study aimed to identify how accurately the current clinical atrial fibrillation (AF) classifications reflect its temporal persistence.
BACKGROUND: Clinical classification of AF is employed to communicate its persistence, to select appropriate therapies, and as inclusion criterion for clinical trials.
METHODS: Cardiac rhythm histories of 1,195 patients (age 73.0 ± 10.1 years, follow-up: 349 ± 40 days) with implantable devices were reconstructed and analyzed. Patients were classified as having paroxysmal or persistent AF by physicians at baseline in accordance with current guidelines. AF burden, measured as the proportion of time spent in AF, was obtained from the device. Additionally we evaluated the agreement between clinical and device-derived AF classifications.
RESULTS: Patients within the same clinical class were highly heterogeneous with regards to AF temporal persistence. Agreement between the clinical AF classification and the objective device-derived assessments of AF temporal persistence was poor (Cohen's kappa: 0.12 [95% CI: 0.05 to 0.18]). Patient characteristics influenced the clinical decision to classify AF as paroxysmal or persistent. Higher ejection fraction (odds ratio: 0.97/per unit [95% CI: 0.95 to 0.98/per unit]; p < 0.0001) and presence of coronary artery disease (odds ratio: 0.53 [95% CI: 0.32 to 0.88]; p = 0.01) were independently associated with a lower probability of being classified as persistent AF for the same AF burden level.
CONCLUSIONS: The currently used clinical AF classifications poorly reflect AF temporal persistence. Patient characteristics significantly influence the physician's classification of AF. Patients classified in identical clinical categories may be inherently heterogeneous with regard to AF temporal persistence. Further study is required to determine if patient selection on the basis of objective criteria derived from rigorous AF monitoring can improve reported outcomes and better identify responders and non-responders to treatments. (OMNI Study-Assessing Therapies in Medtronic Pacemaker, Defibrillator, and Cardiac Resynchronization Therapy Devices; NCT00277524; TRENDS: A Prospective Study of the Clinical Significance of Atrial Arrhythmias Detected by Implanted Device Diagnostics; NCT00279981).
Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  arrhythmia; atrial fibrillation; monitoring

Mesh:

Year:  2014        PMID: 24814497     DOI: 10.1016/j.jacc.2014.04.019

Source DB:  PubMed          Journal:  J Am Coll Cardiol        ISSN: 0735-1097            Impact factor:   24.094


  36 in total

1.  Atrial Fibrillation Burden Signature and Near-Term Prediction of Stroke: A Machine Learning Analysis.

Authors:  Lichy Han; Mariam Askari; Russ B Altman; Susan K Schmitt; Jun Fan; Jason P Bentley; Sanjiv M Narayan; Mintu P Turakhia
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2019-10-15

2.  Atrial fibrillation variability on long-term monitoring of implantable cardiac rhythm management devices.

Authors:  Rachel M Kaplan; Paul D Ziegler; Jodi Koehler; Taya V Glotzer; Rod S Passman
Journal:  Clin Cardiol       Date:  2017-08-11       Impact factor: 2.882

3.  Association of of Atrial Fibrillation Clinical Phenotypes With Treatment Patterns and Outcomes: A Multicenter Registry Study.

Authors:  Taku Inohara; Peter Shrader; Karen Pieper; Rosalia G Blanco; Laine Thomas; Daniel E Singer; James V Freeman; Larry A Allen; Gregg C Fonarow; Bernard Gersh; Michael D Ezekowitz; Peter R Kowey; James A Reiffel; Gerald V Naccarelli; Paul S Chan; Benjamin A Steinberg; Eric D Peterson; Jonathan P Piccini
Journal:  JAMA Cardiol       Date:  2018-01-01       Impact factor: 14.676

4.  2017 ISHNE-HRS expert consensus statement on ambulatory ECG and external cardiac monitoring/telemetry.

Authors:  Jonathan S Steinberg; Niraj Varma; Iwona Cygankiewicz; Peter Aziz; Paweł Balsam; Adrian Baranchuk; Daniel J Cantillon; Polychronis Dilaveris; Sergio J Dubner; Nabil El-Sherif; Jaroslaw Krol; Malgorzata Kurpesa; Maria Teresa La Rovere; Suave S Lobodzinski; Emanuela T Locati; Suneet Mittal; Brian Olshansky; Ewa Piotrowicz; Leslie Saxon; Peter H Stone; Larisa Tereshchenko; Mintu P Turakhia; Gioia Turitto; Neil J Wimmer; Richard L Verrier; Wojciech Zareba; Ryszard Piotrowicz
Journal:  Ann Noninvasive Electrocardiol       Date:  2017-05       Impact factor: 1.468

5.  Risk factors for recurrence of atrial fibrillation.

Authors:  Antoniya Kisheva; Yoto Yotov
Journal:  Anatol J Cardiol       Date:  2021-05       Impact factor: 1.596

Review 6.  Ablation of atrial fibrillation.

Authors:  Matthew Wright; Sanjiv M Narayan
Journal:  Trends Cardiovasc Med       Date:  2014-12-04       Impact factor: 6.677

Review 7.  New approaches to managing nonvalvular atrial fibrillation: what are the thromboembolic implications?

Authors:  Peter J Kudenchuk
Journal:  J Thromb Thrombolysis       Date:  2015-04       Impact factor: 2.300

8.  Recurrent Post-Ablation Paroxysmal Atrial Fibrillation Shares Substrates With Persistent Atrial Fibrillation : An 11-Center Study.

Authors:  Junaid A B Zaman; Tina Baykaner; Paul Clopton; Vijay Swarup; Robert C Kowal; James P Daubert; John D Day; John Hummel; Amir A Schricker; David E Krummen; Moussa Mansour; Gery F Tomassoni; Kevin R Wheelan; Mohan Vishwanathan; Shirley Park; Paul J Wang; Sanjiv M Narayan; John M Miller
Journal:  JACC Clin Electrophysiol       Date:  2017-04

9.  Heart failure and central sleep apnea in the era of implantable recorders.

Authors:  Irina Cabac-Pogorevici; Valeriu Revenco
Journal:  Anatol J Cardiol       Date:  2021-04       Impact factor: 1.596

Review 10.  Expert consensus document: Defining the major health modifiers causing atrial fibrillation: a roadmap to underpin personalized prevention and treatment.

Authors:  Larissa Fabritz; Eduard Guasch; Charalambos Antoniades; Isabel Bardinet; Gerlinde Benninger; Tim R Betts; Eva Brand; Günter Breithardt; Gabriela Bucklar-Suchankova; A John Camm; David Cartlidge; Barbara Casadei; Winnie W L Chua; Harry J G M Crijns; Jon Deeks; Stéphane Hatem; Françoise Hidden-Lucet; Stefan Kääb; Nikos Maniadakis; Stephan Martin; Lluis Mont; Holger Reinecke; Moritz F Sinner; Ulrich Schotten; Taunton Southwood; Monika Stoll; Panos Vardas; Reza Wakili; Andy West; André Ziegler; Paulus Kirchhof
Journal:  Nat Rev Cardiol       Date:  2015-12-24       Impact factor: 32.419

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