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Clinical Classifications of Atrial Fibrillation Poorly Reflect Its Temporal Persistence
Open accessAbstract
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).
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In the citing paper
“Reliance on symptoms alone (by patient or physician) may be misleading-both over and underestimating the presence of AF (Charitos et al., 2014).”
From 2017 ISHNE-HRS expert consensus statement on ambulatory ECG and external cardiac monitoring/telemetry (2017) · cites this paper as Charitos et al., 2014
Experimental — accuracy not yet measuredIn the citing paper
“Clinically determined AF patterns do not correspond well to the AF burden measured by long-term ECG monitoring.163”
From 2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS (2016) · cites this paper as [163]
In the citing paper
“Asymptomatic AF is often undiagnosed41 and is likely underdiagnosed in this study as well.”
From Twelve-single nucleotide polymorphism genetic risk score identifies individuals at increased risk for future atrial fibrillation and stroke (2014) · cites this paper as [41]
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MethodSelf-citationRadiofrequency ablation as initial therapy in paroxysmal atrial fibrillation
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BackgroundMinimizing Ventricular Pacing to Reduce Atrial Fibrillation in Sinus-Node Disease
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“Because the duration of AF episodes reflects the degree of electrical derangement in the heart, and this property exists along a continuum [9], it is therefore not surprising that basing therapy on a binary system often leads to unsatisfactory results.”
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ResultSelf-citationNilsson, K. R., Anerao, A., Kong, M. H., Derejko, P., Szili‐Török, T., Goyal, S., Turagam, M. K., Verma, A., & Castellano, S. (2025) · Journal of Clinical Medicine · doi:10.3390/jcm14030693 · Cited by 3
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“However, other studies highlighted the heterogeneity of paroxysmal atrial fibrillation patients, demonstrating that the paroxysmal AF subgroup has the same arrhythmic substrate as non-paroxysmal AF, making it resistant to pulmonary vein isolation (PVI) [17,18].”
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Contemporary management of persistent atrial fibrillation
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“Zudem ist die ärztliche Klassifikation des Patienten-spezifischen Vorhofflimmertyps durchaus fehleranfällig [27], sodass die Aussagekraft dieser Metaanalyse begrenzt ist.”
BackgroundDoes atrial fibrillation pattern affect stroke risk? Data dredging to help the clinician
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Catheter Ablation for Paroxysmal Atrial Fibrillation
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“Recent studies by Charitos et al [4, 5] sought to classify AF patients based on temporal analysis of their recorded fibrillation episodes and introduced a novel measure of AF density to characterise AF recurrence patterns.”
BackgroundWhen is Device-Detected Atrial Fibrillation Actionable?
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“AF can be classified as paroxysmal, persistent, or permanent AF [76].”
Wang, T., Haverkamp, W., & Strodthoff, N. (2026) · Physiological Measurement · doi:10.1088/1361-6579/ae3937 · Cited by 1
“…is key for more fine-grained understanding of arrhythmia subclasses, such as paroxysmal and persistent in the case of atrial fibrillation, and is believed to lead to clinically actionable insights into disease progression and treatment response [Charitos et al., 2014, De Vos et al., 2010].”
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“13 The implications of this proposed classification may be: (1) pathophysiologic—as opposed to the phenotypic classification that correlates with different mechanisms of progression and with different stages of structural changes of the atria in only some AF patients,12 the newly proposed classification includes all A…”
BackgroundDetection and Determination of Protein Network Associated with Atrial Fibrillation Phenotypes
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“showed that the rates of misclassification are up to 21% among the AF phenotypes [15].”
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“Conversely, defining patients based on history and duration of AF appears simple, but in clinical practice is decidedly less so (13).”
BackgroundMethodAli, W. B. (2015) · Clinical Medical Reviews and Case Reports · doi:10.23937/2378-3656/1410043
“[23] reported that AF classification derived from continuous monitoring data reflected the temporal persistence of AF with greater accuracy and with less overlap between the AF classes.”
BackgroundEditor-in-Chief's Picks From 2014: Part One
Fuster, V. (2015) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2014.12.021
Can Implantable Cardiac Devices Be Used to Lower Risk of Stroke?
Wasserlauf, J., & PASSMAN, R. S. (2017) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-017-0554-5
Risk Stratification in Atrial Fibrillation
Shahid, F., Dzeshka, M. S., Shantsila, E., & Lip, G. Y. H. (2018) · Elsevier eBooks · doi:10.1016/b978-0-323-55429-9.00004-2
Ablation of Persistent and Long-Standing Persistent Atrial Fibrillation
Montgomery, J. A., & Michaud, G. F. (2019) · Elsevier eBooks · doi:10.1016/b978-0-323-52992-1.00019-3
Krisai, P., Hämmerle, P., Blum, S., Meyre, P. B., Aeschbacher, S., Melchiorre, P. A. M., Baretella, O., Rodondi, N., Conen, D., Osswald, S., et al. (2020) · Journal of Internal Medicine · doi:10.1111/joim.13168
Role of Catheter Ablation as a First-Line Treatment for Atrial Fibrillation
Masri, I. E., Kayali, S. M., Manolukas, T., & Levine, Y. C. (2020) · Current Treatment Options in Cardiovascular Medicine · doi:10.1007/s11936-020-00840-y
ESC-Leitlinie 2020 zum Vorhofflimmern: Was ist neu, was ist wichtig, was ist zu tun?
Eckardt, L., Wolfes, J., & Ellermann, C. (2021) · Aktuelle Kardiologie · doi:10.1055/a-1464-0646
Szummer, K. E., Pundi, K. N., Perino, A. C., Fan, J., Kothari, M., & Turakhia, M. P. (2021) · American Heart Journal · doi:10.1016/j.ahj.2021.06.002
Editor-in-Chief's Picks From 2014: Part Two
Fuster, V. (2015) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2014.12.022
How to Treat Patients With First-Diagnosed Atrial Fibrillation
Svennberg, E. (2022) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2022.04.059
Nava, A. (2022) · RiuNet (Universitat Politècnica de València) · doi:10.4995/thesis/10251/184778
Ablation of Persistent and Long-Standing Persistent Atrial Fibrillation
Montgomery, J. A., Kowal, J. L., & Michaud, G. F. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-93110-6.00020-7
Device-detektiertes Vorhofflimmern – was nun?
Tönnis, T., Becher, N., Birkemeyer, R., Duncker, D., Eckardt, L., Gröschel, K., Linz, D., Meyer, C. G., Straube, F., Sultan, A., et al. (2025) · Herzschrittmachertherapie + Elektrophysiologie · doi:10.1007/s00399-025-01112-7
Cai, M., Hua, W., Zhang, N., Yang, S., Hu, Y., Gu, M., Niu, H., & Zhang, S. (2020) · Figshare · doi:10.6084/m9.figshare.12299285
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Mandaglio‐Collados, D., Ramos‐Bratos, M. P., Rivera‐Caravaca, J. M., Soler‐Espejo, E., Roldán, V., Lip, G. Y. H., López‐Gálvez, R., & Marín, F. (2026) · European Journal of Preventive Cardiology · doi:10.1093/eurjpc/zwag061 · Cited by 1
Discrimination of atrial fibrillation burden using cardiac magnetic resonance imaging
Gasser, A., Aeschbacher, S., Coslovsky, M., Meier, V., Ruoff, T., Reichlin, T., Roten, L., Rodondi, N., Haller, M. L., Müller, A. F., et al. (2026) · Heart Rhythm O2 · doi:10.1016/j.hroo.2026.03.011
Atrial Fibrillation Burden: Assessment, Clinical Significance, and Therapeutic Implications
Grigoriou, K., Lamprou, V., Ktenopoulos, N., Theofilis, P., Iliakis, P., Vlachakis, P. K., Apostolos, A., Antoniadis, A. P., Fragakis, N., & Karakasis, P. (2026) · Life · doi:10.3390/life16081378 · Cited by 1
“Although these categories are useful in the clinical setting, they only provide a broad description of arrhythmia behavior and fail to capture the dynamic and heterogeneous nature of AF over time [3,6].”
She, Z., Shi, L., Xie, D., Jiang, F., Zhong, C., Cheng, Z., Shuning, J., Xie, H., Li, Y., & Zhou, J. (2026) · Chemical Engineering Journal · doi:10.1016/j.cej.2026.183437
Atrial Fibrillation Burden as an Outcome in Clinical Trials
Andrade, J. G., & Kirchhof, P. F. (2026) · NEJM Evidence · doi:10.1056/evidctw2600179
Metadata
- Authors
- Charitos, E. I., Pürerfellner, H., Glotzer, T. V., & Ziegler, P. D.
- Affiliations
- University of Lübeck (DE)
- Krankenhaus der Elisabethinen (AT)
- Hackensack University Medical Center (US)
- Medtronic (United States) (US)
- Corresponding author
- Charitos, Efstratios I.
- Venue
- Journal of the American College of Cardiology
- Publisher
- Elsevier BV
- Published
- 2014-07
- Volume
- 63
- Issue
- 25
- Pages
- 2840-2848
- ISSN
- 0735-1097 (ISSN-L)
- OpenAlex
- W191924134
- Cited by
- 188
- References
- 35
- Citations by year
- 2026: 10 · 2025: 16 · 2024: 23 · 2023: 11 · 2022: 14 · 2021: 20 · 2020: 15 · 2019: 9 · 2018: 17 · 2017: 18 · 2016: 13 · 2015: 15 · 2014: 7
- FWCI
- 12.12
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of the American College of Cardiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Atrial Fibrillation Management and Outcomes
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac pacing and defibrillation studies
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac Arrhythmias and Treatments
- Keywords
- atrial fibrillation, temporal persistence, clinical classification, paroxysmal atrial fibrillation, persistent atrial fibrillation, atrial fibrillation burden, cardiac implantable electronic devices, ejection fraction, coronary artery disease, patient selection
- MeSH terms
- Aged, Atrial Fibrillation, Equipment Design, Female, Heart Rate, Humans, Male, Middle Aged, Monitoring, Physiologic, Prospective Studies, Treatment Outcome, Cardiac Resynchronization Therapy Devices
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