Literature DB >> 23499279

Usefulness of frequent supraventricular extrasystoles and a high CHADS2 score to predict first-time appearance of atrial fibrillation.

Shinya Suzuki1, Koichi Sagara, Takayuki Otsuka, Hiroto Kano, Shunsuke Matsuno, Hideaki Takai, Tokuhisa Uejima, Yuji Oikawa, Akira Koike, Kazuyuki Nagashima, Hajime Kirigaya, Junji Yajima, Hiroaki Tanabe, Hitoshi Sawada, Tadanori Aizawa, Takeshi Yamashita.   

Abstract

Frequent supraventricular extrasystoles (SVEs) are associated with the subsequent first-time appearance of atrial fibrillation (AF) and ischemic stroke. The aim of this study was to investigate the combined role of SVEs and an AF-related risk score for ischemic stroke, the CHADS2 score, on the occurrence of new AF in patients in sinus rhythm. The Shinken Database 2004-2010 lists 3,263 patients who underwent 24-hour Holter monitoring. A total of 2,589 patients were analyzed, after excluding 674 patients previously diagnosed with AF. Frequent SVEs were defined as ≥102 beats/day (the top quartile) and the presence of a clinical background for a CHADS2 score ≥2 points as a high CHADS2 score. During the mean follow-up period of 571.4 ± 606.4 days, new AF occurred in 38 patients (9.4 per 1,000 patient-years). The incidence of new AF was 2.7 and 37.7 per 1,000 patient-years for patients with nonfrequent SVEs (<102 beats/day) and low CHADS2 scores and those with frequent SVEs and high CHADS2 scores, respectively. Multivariate Cox regression analysis showed that the hazard ratio for frequent SVEs and a high CHADS2 score compared with nonfrequent SVEs and a low CHADS2 score was 9.49 (95% confidence interval 3.20 to 28.15, p <0.001), even after adjustment for gender, age, medications, and echocardiographic parameters. In conclusion, frequent SVEs and a high CHADS2 score independently and synergistically predict the first-time appearance of AF in patients in sinus rhythm, indicating an approximately 10-fold higher risk. Patients meeting these criteria should have more aggressive early intervention for preventing AF.
Copyright © 2013 Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23499279     DOI: 10.1016/j.amjcard.2013.01.335

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  15 in total

1.  Electrophysiological characteristics and catheter ablation of symptomatic focal premature atrial contractions originating from pulmonary veins and non-pulmonary veins.

Authors:  Xingfu Huang; Yanjia Chen; Junhui Xiao; Hongxin Zhao; Yizhen Chen; Shenrong Liu; Liwei He; Zheng Huang; Haobin Zhou; Dingli Xu; Jian Peng
Journal:  Clin Cardiol       Date:  2018-01-25       Impact factor: 2.882

2.  Anticoagulation in patients at high risk of stroke without documented atrial fibrillation. Time for a paradigm shift?

Authors:  Antoni Bayés de Luna; Adrian Baranchuk; Manuel Martínez-Sellés; Pyotr G Platonov
Journal:  Ann Noninvasive Electrocardiol       Date:  2016-12-16       Impact factor: 1.468

Review 3.  Relation of premature atrial complexes with stroke and death: Systematic review and meta-analysis.

Authors:  Bao-Tao Huang; Fang-Yang Huang; Yong Peng; Yan-Biao Liao; Fei Chen; Tian-Li Xia; Xiao-Bo Pu; Mao Chen
Journal:  Clin Cardiol       Date:  2017-08-28       Impact factor: 2.882

4.  Validation of a simple method for atrial fibrillation screening in patients with stroke.

Authors:  C Gandolfo; M Balestrino; C Bruno; C Finocchi; N Reale
Journal:  Neurol Sci       Date:  2015-04-30       Impact factor: 3.307

5.  Prevalence and predictors of atrial fibrillation in patients with embolic stroke of undetermined source: a real-life single-center retrospective study.

Authors:  Fabio Melis; Marilena Guido; Claudia Amellone; Marco Suppo; Maria Bonanno; Consuelo Bovio; Andrea Pessia; Katia Savio; Maria Teresa Lucciola; Elisa Ebrille; Giulia Guastamacchia; Daniela Cassano; Paola Filippi; Eva Milano; Massimo Giammaria; Daniele Imperiale
Journal:  Neurol Sci       Date:  2021-01-14       Impact factor: 3.307

6.  A Clinical Score for Predicting Atrial Fibrillation in Patients with Cryptogenic Stroke or Transient Ischemic Attack.

Authors:  Calvin Kwong; Albee Y Ling; Michael H Crawford; Susan X Zhao; Nigam H Shah
Journal:  Cardiology       Date:  2017-06-28       Impact factor: 1.869

Review 7.  Use of Prolonged Cardiac Rhythm Monitoring to Identify Atrial Fibrillation After Cryptogenic Stroke.

Authors:  Alexis T Roy; Lee H Schwamm; Aneesh B Singhal
Journal:  Curr Cardiol Rep       Date:  2022-02-16       Impact factor: 2.931

Review 8.  Electrocardiogram (ECG) for the Prediction of Incident Atrial Fibrillation: An Overview.

Authors:  Yoshifusa Aizawa; Hiroshi Watanabe; Ken Okumura
Journal:  J Atr Fibrillation       Date:  2017-12-31

9.  A Detector for Premature Atrial and Ventricular Complexes.

Authors:  Guadalupe García-Isla; Luca Mainardi; Valentina D A Corino
Journal:  Front Physiol       Date:  2021-06-16       Impact factor: 4.566

10.  Prediction of Atrial Fibrillation in a Racially Diverse Cohort: The Multi-Ethnic Study of Atherosclerosis (MESA).

Authors:  Alvaro Alonso; Nicholas S Roetker; Elsayed Z Soliman; Lin Y Chen; Philip Greenland; Susan R Heckbert
Journal:  J Am Heart Assoc       Date:  2016-02-23       Impact factor: 5.501

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