Comparison with the algorithmic methods for AP localization
Majority of AP localization algorithms were based on a limited number of
cases, often partially pre-selected. For example, the sample size was
120, 157, 140, 135, 93 and 148 in Ferrari et al., Boersma et al, D’Avila
et al., Arruda et al., Fitzpatrick et al., and Millstein et al.
algorithms, respectively. (10-13;15;16) Small sample size can create an
illusion that a particular QRS pattern is 100% specific for some
location – as it is not seen at other AP locations. However, a bigger
sample might show that other cases with the same ECG pattern had
successful ablation at other locations as well. The current study, based
on the largest cohort of overt AP ever studied, fully supports the
concept that preexcited ECG pattern does not point to a particular
location but rather reflects a wider area, albeit with the site of
maximum AP frequency surrounded by a probability gradient.
Representative illustration of this phenomenon can be found onSupplementary Figure 4 , which presents outcomes of analysis of
the same ECG with the D’Avila algorithm and with WPW24.com app.
Algorithms are trying to create an ideal match between AP location and
QRS pattern. Imperfections of that match are covered by algorithm’s
sensitivity and specificity. Several independent validation studies
showed that sensitivity/specificity/accuracy of algorithmic methods are
lower than initially reported. These studies are in agreement with the
current results, because low accuracy of an algorithm indicates that the
APs were not limited to the single predicted locations but probably
there was a wider spread of APs. Consequently, algorithmic methods are a
somewhat misleading by creating an illusion of single location even when
their sensitivity, specificity and accuracy are low - indicating
contrariwise. In contrast, WPW24.com, instead of pretending precision
and pointing to one location is showing where the accessory pathways
were actually ablated in all studied cases with the QRS pattern that is
similar or identical to the one with which the current patient had
presented.
Almost all algorithms are based on the analysis of baseline preexcited
ECG, occasionally, on ‘most preexcited’ baseline ECG – that is on a QRS
morphology that results from fusion between native conduction and AP
conduction. That might be another reason for the divergence between the
original studies and the independent validation studies – as the degree
of preexcitation for the same localization varies and it is impossible
to determine how much preexcited ECGs were used in the original study.
Full preexcitation pattern maximizes the localizing information
contained in the preexcited QRS polarity because the confounding impact
of conduction via His-Purkinje system on QRS is nearly eliminated.
Moreover, full preexcitation standardizes the ECG patterns for
comparison between studies. It was shown in our previous work that using
fully preexcited ECG increases accuracy of AP localization, even for
algorithms that were designed for analysis of baseline preexcitation.
(6)