Download Differentiating Paroxysmal From Persistent Atrial Fibrillation

Journal of the American College of Cardiology
Ó 2014 by the American College of Cardiology Foundation
Published by Elsevier Inc.
EDITORIAL COMMENT
Differentiating
Paroxysmal From
Persistent Atrial Fibrillation
Long-Term Electrocardiographic
Monitoring Is Mightier Than the
Clinician*
Suneet Mittal, MD
Ridgewood, New Jersey
Atrial fibrillation (AF) is the most common sustained
arrhythmia encountered in clinical practice. In caring for a
patient with AF, a clinician must establish the pattern of
arrhythmia, determine associated symptoms, and assess for
underlying comorbidities in order to define a short- and
long-term management strategy. Current clinical guidelines
advocate differentiating between paroxysmal, persistent,
long-standing persistent, and permanent patterns of AF (1).
Although it is recognized that these categories are not
mutually exclusive, these guidelines suggest that it is practical to categorize a given patient by his or her most frequent
pattern of presentation.
See page 2840
An implicit premise is that a clinician can accurately
determine a patient’s pattern of AF, presumably through a
combination of history taking and available electrocardiographic (ECG) information. However, in this issue of
the Journal, Charitos et al. (2) provide compelling evidence
to challenge this premise. They evaluated 1,195 patients
(from the OMNI and TRENDS studies) (3,4) with a history of nonpermanent AF who were undergoing implantation of a pacemaker or defibrillator system (from a single
manufacturer) that incorporated an atrial lead. Just prior
to device implantation, the patient’s clinician was asked to
classify whether their patient had paroxysmal or persistent AF.
The patients were then followed to a maximum of 365 days
(minimum follow-up 180 days). Patients who underwent a
*Editorials published in the Journal of the American College of Cardiology reflect the
views of the authors and do not necessarily represent the views of JACC or the
American College of Cardiology.
From the Electrophysiology Laboratory, Arrhythmia Institute of the Valley
Hospital Health System, Ridgewood, New Jersey. Dr. Mittal is a consultant to
Biotronik, Boston Scientific, Medtronic, Scottcare, and St. Jude Medical; and has
received a research grant from Biosense Webster.
Vol. 63, No. 25, 2014
ISSN 0735-1097/$36.00
http://dx.doi.org/10.1016/j.jacc.2014.04.020
specific intervention for AF (e.g., cardioversion, catheter
ablation) during follow-up were subsequently excluded.
The clinician-defined pattern of AF was compared to
device-derived classification, which served as the gold standard. Specifically, based on device data, patients were
stratified as having no AF (no day with >5 min of AF),
paroxysmal AF (at least 1 day of AF but <7 consecutive days
with >23 h of AF), persistent AF (at least 7 consecutive
days with >23 h of AF), and permanent AF (all days with
>23 h of AF). In addition, the authors determined: 1) the
burden of AF, defined as the proportion of the monitored
time a patient was in AF; and 2) the density of AF, defined
as the temporal aggregation of AF burden. The latter is
represented by an index that can range from 0 (low density;
AF is distributed evenly over the monitored period) to 1
(high density; a continuous single episode of AF).
Several important findings emerged from this study. First,
although the study only included patients with a known
history of AF and excluded patients with permanent AF,
399 (33%) patients had no AF whatsoever and 36 (3%)
patients had continuous AF during follow-up. Second, although patients with persistent AF had a higher burden of
AF than patients with paroxysmal AF, there was large
overlap in the distribution of AF burden across patients
within the 2 (physician-defined) AF classifications. Some
patients with very low burden of AF were classified as having
persistent AF, whereas some patients with very high burden
of AF were classified as having paroxysmal AF. Third, quite
surprisingly, a higher left ventricular ejection fraction and
the presence of coronary disease were independently associated with a lower probability of a patient being classified as
having persistent AF by their physician for the same underlying AF burden. Fourth, device-derived AF data more
accurately reflected the temporal persistence of AF and were
not influenced by patient characteristics. Ultimately, the
correlation between clinical and device-derived classification
of AF temporal persistence was quite poor.
The temporal persistence of AF is used to connote progression of disease. Thus, it is determined in each patient in
order to “group” patients (presumably into a similar stage of
disease) and guide decisions regarding management, including the appropriateness and strategy for catheter ablation
(1,5). In paroxysmal AF, triggers (typically from the pulmonary veins) are thought to be responsible for initiating
AF and thus the pulmonary veins are usually targeted for
ablation; recent guidelines impart a Class I indication for
catheter ablation in patients with symptomatic AF refractory
or intolerant to at least 1 Class I or III antiarrhythmic
medication when a rhythm control strategy is desired (1). In
contrast, as AF progresses to a persistent form, it is thought
that, in addition to the triggers, the substrate becomes
important and likely also needs be targeted for ablation
(5–7). The same guidelines impart a Class IIa indication
for catheter ablation in patients with persistent AF and
a Class IIb indication for ablation in patients with longstanding persistent AF (1).
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JACC Vol. 63, No. 25, 2014
July 1, 2014:2849–51
Mittal
Paroxysmal Versus Persistent Atrial Fibrillation
Recent data suggest that atrial fibrosis, a marker of
the underlying substrate, can be visualized using cardiac
magnetic resonance imaging and used to individualize the
strategy for catheter ablation (8–10). Interestingly, similar to
the findings reported by Charitos et al. (2), clinician derived
assessment of temporal persistence of AF correlates poorly
with the location and extent of atrial fibrosis (8). This may
explain, in part, why some patients with presumed paroxysmal AF respond poorly whereas others with presumed
persistent AF respond favorably to pulmonary vein isolation
alone. In the future, it would be of great interest to correlate
the relationship between more objective data (i.e., devicederived) about the temporal persistence of AF with cardiac
magnetic resonance imaging findings.
When evaluating a patient with AF, there are a number of
parameters that can be assessed. These include the frequency
of episodes, the duration of the longest episode, and the
cumulative burden of episodes. To date, greatest emphasis
has been placed on the longest duration of an individual
episode. This forms the basis of our definitions of paroxysmal, persistent, and long-standing persistent AF, which
have been used as markers of disease progression. In addition, the duration of individual episodes has been used to
assess a patient’s risk of thromboembolism (4,11). Charitos
et al. (2) show us the limitations of this approach. First,
there was a large overlap in AF burden between patients
clinically classified as paroxysmal versus persistent AF.
Second, for incompletely understood reasons, at equivalent
burdens of AF, the clinical classification of paroxysmal
versus persistent AF was heavily influenced by patient
characteristics. In contrast, when using data derived through
continuous long-term ECG recordings, there was a clear
and well-demarcated increase in AF burden as patients
progressed from having no AF to paroxysmal AF (mean
burden 3%) to persistent AF (mean burden 39%) to permanent AF (mean burden 99%), which appears more
reflective of disease progression.
In this study, an implanted atrial lead was used to derive
device based ECG data. However, this is not feasible in the
vast majority of AF patients. Available options for obtaining
ECG data in most patients range from a variety of available
ambulatory external ECG recording systems to implantable
loop recorders (12,13). Charitos et al. (14) have previously
offered us important insights into the optimal frequency and
method of ECG monitoring. In particular, the duration of
monitoring is fundamentally dependent on the patient’s
burden and density of AF. Unfortunately, neither of these
parameters is known nor can be predicted in any given patient. Patients with high-density AF require more frequent
ECG monitoring to achieve higher AF detection sensitivity
than patients with low density AF, especially when the AF
burden is <40% (14). However, the frequency and duration
of external ECG monitoring necessary to optimize diagnostic yield is impractical due to difficulty with patient
compliance and restrictive coverage policies of insurance
providers.
There are 2 promising options to address the long-term
ECG needs of this patient population. The first option is
to consider implantation of a stand-alone loop recorder for
long-term ECG monitoring. These devices, which have
recently become miniaturized to the point of being potentially implantable in an office setting, have dedicated algorithms that determine the presence of absence of AF and
can provide information (wirelessly and remotely) about
the longest episode and burden of AF (15). The other is
to continue our investigation of “smartphone” based ECG
applications, which have proven feasible as a tool for community wide screening of AF (16). A daily check of the
ECG may provide a reasonable qualitative assessment of
the AF burden and allow for more precise clinical discrimination between paroxysmal and persistent patterns of
disease. However, the reliance on patient compliance and
inability to precisely quantify either the duration of longest
AF episode and actual burden of AF may be important
limitations.
The current study is not without its limitations. Had the
OMNI and TRENDS investigators known that this was
an additional aim of these studies, they may have attempted
to more accurately determine the temporal pattern of AF in
their patients. In addition, it is possible that in some patients
AF actually progressed during the 1-year observation period.
Finally, patients undergoing implantation of a pacemaker
or defibrillator with an atrial lead may not be representative
of the overall universe of AF patients. Nonetheless, the
authors are correct in stating that clinical decisions (rate
vs. rhythm control; antiarrhythmic medications vs. catheter
ablation; choice of lesion sets during ablation) are routinely
being made based on clinical classifications of the temporal
persistence of AF, which appear to have limited accuracy.
Charitos and colleagues have again highlighted the importance and necessity of long-term ECG recordings to more
objectively, and thus more accurately, classify the temporal
persistence of AF in any given patient. Whether this can be
adequately accomplished without an implantable system
needs further investigation.
Reprint requests and correspondence: Dr. Suneet Mittal, Electrophysiology Laboratory, The Valley Hospital, 223 North Van
Dien Avenue, Ridgewood, New Jersey 07450. E-mail: mittsu@
valleyhealth.com.
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Key Words: arrhythmia
-
atrial fibrillation
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monitoring.