AIMS: Atrial fibrillation (AF) is the most common
rhythm disorder. Because of the high recurrence rate of
AF after cardioversion and because of potential side
effects of electrical cardioversion, it is clinically
important to predict persistence of sinus rhythm after
electrical cardioversion before it is attempted. The
aim of our study was the development of a mathematical
model by 'genetic' programming (GP), a
non-deterministic modelling technique, which would
predict maintenance of sinus rhythm after electrical
cardioversion of persistent AF. PATIENTS AND METHODS:
Ninety-seven patients with persistent AF lasting more
than 48 h, undergoing the first attempt at
transthoracic cardioversion were included in this
prospective study. Persistence of AF before the
cardioversion attempt, amiodarone treatment, left
atrial dimension, mean, standard deviation and
approximate entropy of ECG R-R intervals were
collected. The data of 53 patients were randomly
selected from the database and used for GP modelling;
the other 44 data sets were used for model
testing.
RESULTS: In 23 patients sinus rhythm persisted at 3
months. In the other 21 patients sinus rhythm was not
achieved or its duration was less than 3 months. The
model developed by GP failed to predict maintenance of
sinus rhythm at 3 months in one patient and in six
patients falsely predicted maintenance of sinus rhythm.
Positive and negative likelihood ratios of the model
for testing data were 4.32 and 0.05, respectively.
Using this model 15 of 21 (71.4per cent) cardioversions
not resulting in sinus rhythm at 3 months would have
been avoided, whereas 22 of 23 (95.6per cent)
cardioversions resulting in sinus rhythm at 3 months
would have been administered.
CONCLUSION: This model developed by GP, including
clinical data, ECG data from the time-domain and
nonlinear dynamics can predict maintenance of sinus
rhythm. Further research is needed to explore its
utility in the present or an expanded form.
http://europace.oxfordjournals.org/content/vol7/issue5/index.dtl
Cardiology Department, Hospital Celje Slovenia;
Laboratory for Intelligent Manufacturing Systems,
Faculty of Mechanical Engineering Maribor, Slovenia;
Department for Intensive Internal Medicine, General
Hospital Celje Oblakova 5 3000 Celje, Slovenia
World Congress of Cardiology
Copyright 2006 European Heart Rhythm Association of the
European Society of Cardiology (ESC)
%0 Journal Article
%1 Zohara:2005:E
%A Zohara, Petra
%A Kovacic, Miha
%A Brezocnik, Miran
%A Podbregar, Matej
%D 2005
%J Europace
%K algorithms, atrial cardioversion, electrical fibrillation, genetic prediction programming,
%N 5
%P 500--507
%R doi:10.1016/j.eupc.2005.04.007
%T Prediction of maintenance of sinus rhythm after
electrical cardioversion of atrial fibrillation by
non-deterministic modelling
%V 7
%X AIMS: Atrial fibrillation (AF) is the most common
rhythm disorder. Because of the high recurrence rate of
AF after cardioversion and because of potential side
effects of electrical cardioversion, it is clinically
important to predict persistence of sinus rhythm after
electrical cardioversion before it is attempted. The
aim of our study was the development of a mathematical
model by 'genetic' programming (GP), a
non-deterministic modelling technique, which would
predict maintenance of sinus rhythm after electrical
cardioversion of persistent AF. PATIENTS AND METHODS:
Ninety-seven patients with persistent AF lasting more
than 48 h, undergoing the first attempt at
transthoracic cardioversion were included in this
prospective study. Persistence of AF before the
cardioversion attempt, amiodarone treatment, left
atrial dimension, mean, standard deviation and
approximate entropy of ECG R-R intervals were
collected. The data of 53 patients were randomly
selected from the database and used for GP modelling;
the other 44 data sets were used for model
testing.
RESULTS: In 23 patients sinus rhythm persisted at 3
months. In the other 21 patients sinus rhythm was not
achieved or its duration was less than 3 months. The
model developed by GP failed to predict maintenance of
sinus rhythm at 3 months in one patient and in six
patients falsely predicted maintenance of sinus rhythm.
Positive and negative likelihood ratios of the model
for testing data were 4.32 and 0.05, respectively.
Using this model 15 of 21 (71.4per cent) cardioversions
not resulting in sinus rhythm at 3 months would have
been avoided, whereas 22 of 23 (95.6per cent)
cardioversions resulting in sinus rhythm at 3 months
would have been administered.
CONCLUSION: This model developed by GP, including
clinical data, ECG data from the time-domain and
nonlinear dynamics can predict maintenance of sinus
rhythm. Further research is needed to explore its
utility in the present or an expanded form.
@article{Zohara:2005:E,
abstract = {AIMS: Atrial fibrillation (AF) is the most common
rhythm disorder. Because of the high recurrence rate of
AF after cardioversion and because of potential side
effects of electrical cardioversion, it is clinically
important to predict persistence of sinus rhythm after
electrical cardioversion before it is attempted. The
aim of our study was the development of a mathematical
model by 'genetic' programming (GP), a
non-deterministic modelling technique, which would
predict maintenance of sinus rhythm after electrical
cardioversion of persistent AF. PATIENTS AND METHODS:
Ninety-seven patients with persistent AF lasting more
than 48 h, undergoing the first attempt at
transthoracic cardioversion were included in this
prospective study. Persistence of AF before the
cardioversion attempt, amiodarone treatment, left
atrial dimension, mean, standard deviation and
approximate entropy of ECG R-R intervals were
collected. The data of 53 patients were randomly
selected from the database and used for GP modelling;
the other 44 data sets were used for model
testing.
RESULTS: In 23 patients sinus rhythm persisted at 3
months. In the other 21 patients sinus rhythm was not
achieved or its duration was less than 3 months. The
model developed by GP failed to predict maintenance of
sinus rhythm at 3 months in one patient and in six
patients falsely predicted maintenance of sinus rhythm.
Positive and negative likelihood ratios of the model
for testing data were 4.32 and 0.05, respectively.
Using this model 15 of 21 (71.4per cent) cardioversions
not resulting in sinus rhythm at 3 months would have
been avoided, whereas 22 of 23 (95.6per cent)
cardioversions resulting in sinus rhythm at 3 months
would have been administered.
CONCLUSION: This model developed by GP, including
clinical data, ECG data from the time-domain and
nonlinear dynamics can predict maintenance of sinus
rhythm. Further research is needed to explore its
utility in the present or an expanded form.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Zohara, Petra and Kovacic, Miha and Brezocnik, Miran and Podbregar, Matej},
biburl = {https://www.bibsonomy.org/bibtex/2882c7e7672b4c4e4c47d2c9c983b6e77/brazovayeye},
doi = {doi:10.1016/j.eupc.2005.04.007},
interhash = {397a80071fef212bd151b84ed85e3622},
intrahash = {882c7e7672b4c4e4c47d2c9c983b6e77},
issn = {1532-2092},
journal = {Europace},
keywords = {algorithms, atrial cardioversion, electrical fibrillation, genetic prediction programming,},
notes = {http://europace.oxfordjournals.org/content/vol7/issue5/index.dtl
Cardiology Department, Hospital Celje Slovenia;
Laboratory for Intelligent Manufacturing Systems,
Faculty of Mechanical Engineering Maribor, Slovenia;
Department for Intensive Internal Medicine, General
Hospital Celje Oblakova 5 3000 Celje, Slovenia
World Congress of Cardiology
Copyright 2006 European Heart Rhythm Association of the
European Society of Cardiology (ESC)},
number = 5,
pages = {500--507},
timestamp = {2008-06-19T17:55:59.000+0200},
title = {Prediction of maintenance of sinus rhythm after
electrical cardioversion of atrial fibrillation by
non-deterministic modelling},
volume = 7,
year = 2005
}