Prediction of maintenance of sinus rhythm after electrical cardioversion of atrial fibrillation by non-deterministic modelling

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Zohara:2005:E,
  author =       "Petra Zohara and Miha Kovacic and Miran Brezocnik and 
                 Matej Podbregar",
  title =        "Prediction of maintenance of sinus rhythm after
                 electrical cardioversion of atrial fibrillation by
                 non-deterministic modelling",
  journal =      "Europace",
  year =         "2005",
  volume =       "7",
  number =       "5",
  pages =        "500--507",
  keywords =     "genetic algorithms, genetic programming, atrial
                 fibrillation, electrical cardioversion, prediction",
  ISSN =         "1532-2092",
  DOI =          "doi:10.1016/j.eupc.2005.04.007",
  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.",
  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)",
}

Genetic Programming entries for Petra Zohara Miha Kovacic Miran Brezocnik M Podbregar

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