In the present study, we found that PWDis and
PTFV
1 parameters as measured on surface ECG were
independent predictors for the presence of PAF in
patients with ischemic stroke.
Some patients with AF describe palpitations,
shortness of breath and fatigue while some
may be completely asymptomatic and present
with complications such as ischemic stroke or
tachycardiomyopathy.[8] Non-valvular AF is
responsible for about half of all cardioembolic
events.[9] The incidence of occult or subclinical AF is
not known. Therefore, patients with symptomatic AF
that are observed in daily practice may be considered
the tip of the iceberg. The development of new
devices and applications has led to an increase in
diagnosis rates of asymptomatic and subclinical AF.
The rates of subclinical AF was reported to be 35%
in a group of patients with implanted cardiac devices
that were followed for 2.5 years.[10] In patients with
cryptogenic stroke, 12.5% were found to have PAF
attacks during one-year rhythm monitorization.[11]
It is important to identify patients who do not have
arrhythmia on surface ECG, but who are at high risk
for the development of AF and to perform long-term
rhythm monitoring in these patients to prevent
ischemic stroke.
Many scoring methods have been utilized to
predict the development of AF in those with normal
surface ECG.[6,7] The CHADS2 and the CHA2DS2-
VASc risk scores have been reported for prediction of
new occurrence of AF, ischemic stroke and long-term
outcomes after AF ablation.[12] Christophersen et al.[12] reported that CHARGE-AF scoring was better
at predicting AF, compared to CHA2DS2-VASc.
On the other hand, some studies have used the
HATCH score for prediction of AF recurrence and
persistence.[13] The main feature of these scoring
methods is that they predict the development of
AF according to the clinical characteristics of the
patients. However, AF is an ECG disorder and
using ECG findings for its prediction may be a more
plausible way. Electrocardiographic evaluation is also
a simpler, cheaper, and easily accessible method than
the aforementioned scoring systems. Furthermore, it
has been reported that P-wave indices are as effective
as clinical scoring methods for the prediction of AF
and ischemic stroke.[14] Several ECG indices thought
to represent atrial remodeling have been independently
associated with stroke and AF.[15] These measures
include the (i) PWD; (ii) PWDis; (iii) PTFV1 in the
precordial lead V1; (iv) P-wave axis; and (v) interatrial
blocks (IABs).[16] Previous studies have identified
several P-wave indices that are markers of LA
dysfunction and are associated with ischemic stroke
with or without AF.[17] Previous studies have reported
that maximum PWD may be used for the prediction
of AF.[18] However, we did not detect PWD to be a
predictor for the presence of AF in our study.
P wave dispersion is considered to reflect impaired
and heterogeneous interatrial conduction, which is a
specific and sensitive marker of AF in a wide variety of
conditions.[19] Dilaveris et al.[18] found that PWDis was
significantly higher in patients with paroxysmal AF
compared to the control group, and a PWDis value of
40 ms distinguished paroxysmal AF patients from the
control group with a sensitivity of 83% and a specificity
of 85%. Aytemir et al.[20] reported PWDis >36 ms to
be an independent predictor for the development of
AF with a sensitivity of 77% and specificity of 82%.
The PWDis has been used for the prediction of AF
in several clinical situations such as hyperthyroidism,
chronic obstructive pulmonary disease, acute ischemic
stroke and hypertrophic cardiomyopathy.[19] Doğan et
al.[15] reported PWDis as an independent predictor
for the development of AF in patients with acute
ischemic stroke. Similarly, we also found PWDis to
be a predictor of PAF in patients with ischemic stroke,
with a sensitivity of 71% and specificity of 69%.
The PTFV1 was first used by Morris et al.[21]
in 1964 as a representative of LA overload in
several valvular heart diseases. Later, PTFV1 was
found to be an indicator of various pathologies such as increased LA pressure, LA hypertrophy, LA
enlargement, and abnormal interatrial conduction.[17]
Since AF development is also associated with these
structural changes and electrical remodeling, PTFV1
may be a good predictor of AF development. PTFV1
>4000 μV·ms is accepted to be abnormal. An
abnormal PTFV1 level has been shown to negatively
affect prognosis in heart failure and myocardial
infarction.[22] It was reported that a 1-SD increase
of PTFV1 increased the risk of AF occurrence by
27%.[17] Additionally, PTFV1 was found to be a
better predictor in hemodialysis and stroke patients
compared to the normal population.[17] The PTFV1 is
indicative of LA volume overload and it has, therefore,
been frequently used for AF prediction in patients
undergoing hemodialysis.[17] Goda et al.[23] found
PTFV1 to be a strong predictor of AF in patients
with acute ischemic stroke. In addition, PTFV1 was
reported to be a good predictor of stroke, regardless
of AF in a meta-analysis by He et al.[24] However,
Sajeev et al.[25] suggested that PTFV1 was a weak
predictor of ischemic stroke. Similarly, we found that
PTFV1 had a lower sensitivity and specificity in the
detection of AF compared to PWDis.
There are some limitations in the current study.
First, our sample size was relatively small, which may
have weakened the strength of our results. Second,
this study is retrospective in nature. Third, Holter
ECG monitoring was performed for 24 to 48 h in all
patients. If a longer follow-up could have been made,
PAF attacks could have been detected in more patients.
In conclusion, PWDis and PTFV1 in lead V1 are
independent predictors for the presence of PAF in
patients with ischemic stroke. These simple and easily
accessible predictors, which can be detected by surface
ECG, may help in identifying patients that require
longer rhythm monitoring to detect occult PAFs,
thereby preventing recurrent strokes.
Declaration of conflicting interests
The authors declared no conflicts of interest with respect
to the authorship and/or publication of this article.
Funding
The authors received no financial support for the research
and/or authorship of this article.
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