• About
  • Policies
  • What is openaccess
  • Library
  • Contact
Advanced search
      View Item 
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Engineering
      • Department of Computer Engineering
      • View Item
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Engineering
      • Department of Computer Engineering
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Predictors of sinus rhythm after electrical cardioversion of atrial fibrillation: results from a data mining project on the Flec-SL trial data set

      Thumbnail
      View / Download
      345.0 Kb
      Author
      Oto, E.
      Okutucu, S.
      Katircioglu-Öztürk, D.
      Güvenir, H. A.
      Karaagaoglu, E.
      Borggrefe, M.
      Breithardt, G.
      Goette, A.
      Ravens, U.
      Steinbeck, G.
      Wegscheider, K.
      Oto, A.
      Kirchhof, P.
      Date
      2017
      Source Title
      Europace
      Print ISSN
      1099-5129
      Publisher
      Oxford University Press
      Volume
      19
      Issue
      6
      Pages
      921 - 928
      Language
      English
      Type
      Article
      Item Usage Stats
      123
      views
      162
      downloads
      Abstract
      Data mining is the computational process to obtain information from a data set and transform it for further use. Herein, through data mining with supportive statistical analyses, we identified and consolidated variables of the Flecainide Short-Long (Flec-SL—AFNET 3) trial dataset that are associated with the primary outcome of the trial, recurrence of persistent atrial fibrillation (AF) or death. Methods and results: The ‘Ranking Instances by Maximizing the Area under the ROC Curve’ (RIMARC) algorithm was applied to build a classifier that can predict the primary outcome by using variables in the Flec-SL dataset. The primary outcome was time to persistent AF or death. The RIMARC algorithm calculated the predictive weights of each variable in the Flec-SL dataset for the primary outcome. Among the initial 21 parameters, 6 variables were identified by the RIMARC algorithm. In univariate Cox regression analysis of these variables, increased heart rate during AF and successful pharmacological conversion (PC) to sinus rhythm (SR) were found to be significant predictors. Multivariate Cox regression analysis revealed successful PC as the single relevant predictor of SR maintenance. The primary outcome risk was 3.14 times (95% CI:1.7–5.81) lower in those who had successful PC to SR than those who needed electrical cardioversion. Conclusions: Pharmacological conversion of persistent AF with flecainide without the need for electrical cardioversion is a powerful and independent predictor of maintenance of SR. A strategy of flecainide pretreatment for 48 h prior to planned electrical cardioversion may be a useful planning of a strategy of long-term rhythm control.
      Keywords
      Atrial fibrillation
      Cardioversion
      Data mining
      Flecainide
      RIMARC algorithm
      Permalink
      http://hdl.handle.net/11693/37157
      Published Version (Please cite this version)
      http://dx.doi.org/10.1093/europace/euw144
      Collections
      • Department of Computer Engineering 1408
      Show full item record

      Browse

      All of BUIRCommunities & CollectionsTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartmentsThis CollectionTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartments

      My Account

      Login

      Statistics

      View Usage StatisticsView Google Analytics Statistics

      Bilkent University

      If you have trouble accessing this page and need to request an alternate format, contact the site administrator. Phone: (312) 290 1771
      © Bilkent University - Library IT

      Contact Us | Send Feedback | Off-Campus Access | Admin | Privacy