Literature DB >> 33514633

Proposed A2C2S2-VASc score for predicting atrial fibrillation development in patients with atrial flutter.

Yung-Lung Chen1,2, Hui-Ting Wang3, Huang-Chung Chen1, Wen-Hao Liu1, Shaur-Zheng Chong1, Shu-Kai Hsueh1, Chang-Ming Chung4, Yu-Shen Lin5.   

Abstract

AIMS: The clinical outcome and threshold of oral anticoagulation differs between patients with solitary atrial flutter (AFL) and those with AFL developing atrial fibrillation (AF) (AFL-DAF). We therefore investigated previously unevaluated predictors of AF development in patients with AFL, and also the predictive values of risk scores in predicting the occurrence of AF and ischaemic stroke. METHODS AND
RESULTS: Participants were those diagnosed with AFL between 1 January 2001 and 31 December 2013. Patients were classified into solitary AFL and AFL-DAF groups during follow-up. Finally, 4101 patients with solitary AFL and 4101 patients with AFL-DAF were included after 1:1 propensity score matching with CHA2DS2-VASc scores and their components, AFL diagnosis year and other comorbidities. The group difference in the prevalence of ischaemic stroke/transient ischaemic attack (TIA) and congestive heart failure (CHF) was substantial, that of vascular disease was moderate, and that of diabetes and hypertension was negligible. Therefore, we reweighted the component of heart failure as 2 (the same with stroke/TIA) and vascular disease as 1 in the proposed A2C2S2-VASc score. The proposed A2C2S2-VASc and CHA2DS2-VASC scores showed patients with AFL who had higher delta scores and follow-up scores had higher risk of AF development. The delta score outperformed the follow-up score in both scoring systems in predicting ischaemic stroke.
CONCLUSION: This study showed that new-onset CHF, stroke/TIA and vascular disease were predictors of AF development in patients with AFL. The dynamic score and changes in both CHA2DS2-VASC and the proposed A2C2S2-VASc score could predict the development of AF and ischaemic stroke. © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.

Entities:  

Keywords:  atrial fibrillation; atrial flutter; heart failure; stroke

Year:  2021        PMID: 33514633      PMCID: PMC7849887          DOI: 10.1136/openhrt-2020-001478

Source DB:  PubMed          Journal:  Open Heart        ISSN: 2053-3624


  19 in total

1.  Validating recommendations for coronary angiography following acute myocardial infarction in the elderly: a matched analysis using propensity scores.

Authors:  S T Normand; M B Landrum; E Guadagnoli; J Z Ayanian; T J Ryan; P D Cleary; B J McNeil
Journal:  J Clin Epidemiol       Date:  2001-04       Impact factor: 6.437

2.  Long-term outcome prediction of CHA2DS2VASc and HATCH scores in a cohort of patients with typical atrial flutter.

Authors:  Javier García Seara; Francisco Gude; Sergio Raposeiras-Roubin; Jose L Martínez Sande; Laila González Melchor; Moisés Rodríguez-Mañero; Xesús Fernández-López; Noelia Bouzas Cruz; Andrea López-López; Belén Alvarez Alvarez; Rami Riziq Yousef Abumuaileq; Rosa Abellas; Diego Iglesias; José Ramón González-Juanatey
Journal:  Int J Cardiol       Date:  2015-06-30       Impact factor: 4.164

3.  HATCH score in the prediction of new-onset atrial fibrillation after catheter ablation of typical atrial flutter.

Authors:  Ke Chen; Rong Bai; Wenning Deng; Chuanyu Gao; Jing Zhang; Xianqing Wang; Shunbao Wang; Haixia Fu; Yonghui Zhao; Jiaying Zhang; Jianzeng Dong; Changsheng Ma
Journal:  Heart Rhythm       Date:  2015-04-04       Impact factor: 6.343

Review 4.  Modifiable Risk Factors and Atrial Fibrillation.

Authors:  Dennis H Lau; Stanley Nattel; Jonathan M Kalman; Prashanthan Sanders
Journal:  Circulation       Date:  2017-08-08       Impact factor: 29.690

5.  Validation of algorithms to identify stroke risk factors in patients with acute ischemic stroke, transient ischemic attack, or intracerebral hemorrhage in an administrative claims database.

Authors:  Sheng-Feng Sung; Cheng-Yang Hsieh; Huey-Juan Lin; Yu-Wei Chen; Yea-Huei Kao Yang; Chung-Yi Li
Journal:  Int J Cardiol       Date:  2016-04-14       Impact factor: 4.164

6.  Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham Heart Study.

Authors:  E J Benjamin; D Levy; S M Vaziri; R B D'Agostino; A J Belanger; P A Wolf
Journal:  JAMA       Date:  1994-03-16       Impact factor: 56.272

7.  Concordance between patient self-reports and claims data on clinical diagnoses, medication use, and health system utilization in Taiwan.

Authors:  Chi-Shin Wu; Mei-Shu Lai; Susan Shur-Fen Gau; Sheng-Chang Wang; Hui-Ju Tsai
Journal:  PLoS One       Date:  2014-12-02       Impact factor: 3.240

8.  Different Implications of Heart Failure, Ischemic Stroke, and Mortality Between Nonvalvular Atrial Fibrillation and Atrial Flutter-a View From a National Cohort Study.

Authors:  Yu-Sheng Lin; Tien-Hsing Chen; Ching-Chi Chi; Ming-Shyan Lin; Tao-Hsin Tung; Chi-Hung Liu; Yung-Lung Chen; Mien-Cheng Chen
Journal:  J Am Heart Assoc       Date:  2017-07-21       Impact factor: 5.501

9.  CHA₂DS₂-VASc Score in the Prediction of Ischemic Stroke in Patients after Radiofrequency Catheter Ablation of Typical Atrial Flutter.

Authors:  Moo Nyun Jin; Changho Song; Tae Hoon Kim; Jae Sun Uhm; Hui Nam Pak; Moon Hyoung Lee; Boyoung Joung
Journal:  Yonsei Med J       Date:  2018-03       Impact factor: 2.759

10.  Comparison of Clinical Outcomes Among Patients With Atrial Fibrillation or Atrial Flutter Stratified by CHA2DS2-VASc Score.

Authors:  Yu-Sheng Lin; Yung-Lung Chen; Tien-Hsing Chen; Ming-Shyan Lin; Chi-Hung Liu; Teng-Yao Yang; Chang-Ming Chung; Mien-Cheng Chen
Journal:  JAMA Netw Open       Date:  2018-08-03
View more
  1 in total

1.  Differential Risk of Dementia Between Patients With Atrial Flutter and Atrial Fibrillation: A National Cohort Study.

Authors:  Hui-Ting Wang; Yung-Lung Chen; Yu-Sheng Lin; Huang-Chung Chen; Shaur-Zheng Chong; Shukai Hsueh; Chang-Ming Chung; Mien-Cheng Chen
Journal:  Front Cardiovasc Med       Date:  2021-11-18
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.