Literature DB >> 21029359

A comparison of risk stratification schemes for stroke in 79,884 atrial fibrillation patients in general practice.

T P Van Staa1, E Setakis, G L Di Tanna, D A Lane, G Y H Lip.   

Abstract

BACKGROUND: Anticoagulation management of patients with atrial fibrillation (AF) should be tailored individually on the basis of ischemic stroke risk. The objective of this study was to compare the predictive ability of 15 published stratification schemes for stroke risk in actual clinical practice in the UK.
METHODS: AF patients aged ≥ 18 years in the General Practice Research Database, which contains computerized medical records, were included. The c-statistic was estimated to determine the predictive ability for stroke for each scheme. Outcomes included stroke, hospitalizations for stroke, and death resulting from stroke (as recorded on death certificates).
RESULTS: The study cohort included 79,844 AF patients followed for an average of 4 years (average of 2.4 years up to the start of warfarin therapy). All risk schemes had modest discriminatory ability in AF patients, with c-statistics for predicting events ranging from 0.55 to 0.69 for strokes recorded by the general practitioner or in hospital, from 0.56 to 0.69 for stroke hospitalizations, and from 0.56 to 0.78 for death resulting from stroke as reported on death certificates. The proportion of patients assigned to individual risk categories varied widely across the schemes, with the proportion categorized as moderate risk ranging from 12.7% (CHA(2) DS(2)-VASc) to 61.5% (modified CHADS(2)). Low-risk subjects were truly low risk (with annual stroke events < 0.5%) with the modified CHADS(2), National Institute for Health and Clinical Excellence and CHA(2) DS(2) -VASc schemes.
CONCLUSION: Current published risk schemes have modest predictive value for stroke. A new scheme (CHA(2) DS(2) -VASc) may discriminate those at truly low risk and minimize classification of subjects as intermediate/moderate risk. This approach would simplify our approach to stroke risk stratification and improve decision-making for thromboprophylaxis in patients with AF.
© 2010 International Society on Thrombosis and Haemostasis.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21029359     DOI: 10.1111/j.1538-7836.2010.04085.x

Source DB:  PubMed          Journal:  J Thromb Haemost        ISSN: 1538-7836            Impact factor:   5.824


  65 in total

Review 1.  Meta-analysis of CHADS2 versus CHA2DS2-VASc for predicting stroke and thromboembolism in atrial fibrillation patients independent of anticoagulation.

Authors:  Wen-Gen Zhu; Qin-Mei Xiong; Kui Hong
Journal:  Tex Heart Inst J       Date:  2015-02-01

Review 2.  Evidence behind quality of care measures for venous thromboembolism and atrial fibrillation.

Authors:  G Eymin; A K Jaffer
Journal:  J Thromb Thrombolysis       Date:  2014       Impact factor: 2.300

3.  Antithrombotic therapy for atrial fibrillation: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines.

Authors:  John J You; Daniel E Singer; Patricia A Howard; Deirdre A Lane; Mark H Eckman; Margaret C Fang; Elaine M Hylek; Sam Schulman; Alan S Go; Michael Hughes; Frederick A Spencer; Warren J Manning; Jonathan L Halperin; Gregory Y H Lip
Journal:  Chest       Date:  2012-02       Impact factor: 9.410

4.  Integrated Machine Learning Approaches for Predicting Ischemic Stroke and Thromboembolism in Atrial Fibrillation.

Authors:  Xiang Li; Haifeng Liu; Xin Du; Ping Zhang; Gang Hu; Guotong Xie; Shijing Guo; Meilin Xu; Xiaoping Xie
Journal:  AMIA Annu Symp Proc       Date:  2017-02-10

5.  Correlation between CHADS2 score and anticoagulant use in atrial fibrillation: Results of a mini-survey.

Authors:  Gerry Cartman; Mark Blostein; Mark J Eisenberg
Journal:  Exp Clin Cardiol       Date:  2013

Review 6.  Left atrial appendage exclusion for prevention of stroke in atrial fibrillation: review of minimally invasive approaches.

Authors:  Joshua D Moss
Journal:  Curr Cardiol Rep       Date:  2014-02       Impact factor: 2.931

7.  Stroke or left atrial thrombus prediction using antithrombin III and mean platelet volume in patients with nonvalvular atrial fibrillation.

Authors:  Seo-Won Choi; Bo-Bae Kim; Dong-Hyun Choi; Geon Park; Byung Chul Shin; Heesang Song; DongHun Kim; Dong-Min Kim
Journal:  Clin Cardiol       Date:  2017-08-14       Impact factor: 2.882

Review 8.  Atrial fibrillation in women: epidemiology, pathophysiology, presentation, and prognosis.

Authors:  Darae Ko; Faisal Rahman; Renate B Schnabel; Xiaoyan Yin; Emelia J Benjamin; Ingrid E Christophersen
Journal:  Nat Rev Cardiol       Date:  2016-04-07       Impact factor: 32.419

9.  Abnormal P-Wave Axis and Ischemic Stroke: The ARIC Study (Atherosclerosis Risk In Communities).

Authors:  Ankit Maheshwari; Faye L Norby; Elsayed Z Soliman; Ryan J Koene; Mary R Rooney; Wesley T O'Neal; Alvaro Alonso; Lin Y Chen
Journal:  Stroke       Date:  2017-06-16       Impact factor: 7.914

10.  The risk stratification in atrial fibrillation.

Authors:  Domenico Prisco; Caterina Cenci; Elena Silvestri; Giacomo Emmi; Tommaso Barnini; Carlo Tamburini
Journal:  Intern Emerg Med       Date:  2012-10       Impact factor: 3.397

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.