Literature DB >> 24929840

The predictive ability of the CHADS2 and CHA2DS2-VASc scores for bleeding risk in atrial fibrillation: the MAQI(2) experience.

Geoffrey D Barnes1, Xiaokui Gu2, Brian Haymart2, Eva Kline-Rogers2, Steve Almany3, Jay Kozlowski4, Dennis Besley5, Gregory D Krol6, James B Froehlich2, Scott Kaatz7.   

Abstract

INTRODUCTION: Guidelines recommend the assessment of stroke and bleeding risk before initiating warfarin anticoagulation in patients with atrial fibrillation. Many of the elements used to predict stroke also overlap with bleeding risk in atrial fibrillation patients and it is tempting to use stroke risk scores to efficiently estimate bleeding risk. Comparison of stroke risk scores to bleeding risk scores to predict bleeding has not been thoroughly assessed.
METHODS: 2600 patients followed at seven anticoagulation clinics were followed from October 2009-May 2013. Five risk models (CHADS2, CHA2DS2-VASc, HEMORR2HAGES, HAS-BLED and ATRIA) were retrospectively applied to each patient. The primary outcome was the first major bleeding event. Area under the ROC curves were compared with C statistic and net reclassification improvement (NRI) analysis was performed.
RESULTS: 110 patients experienced a major bleeding event in 2581.6 patient-years (4.5%/year). Mean follow up was 1.0±0.8years. All of the formal bleeding risk scores had a modest predictive value for first major bleeding events (C statistic 0.66-0.69), performing better than CHADS2 and CHA2DS2-VASc scores (C statistic difference 0.10 - 0.16). NRI analysis demonstrated a 52-69% and 47-64% improvement of the formal bleeding risk scores over the CHADS2 score and CHA2DS2-VASc score, respectively.
CONCLUSIONS: The CHADS2 and CHA2DS2-VASc scores did not perform as well as formal bleeding risk scores for prediction of major bleeding in non-valvular atrial fibrillation patients treated with warfarin. All three bleeding risk scores (HAS-BLED, ATRIA and HEMORR2HAGES) performed moderately well.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Anticoagulants; Atrial Fibrillation; Risk Factors; Stroke; Warfarin

Mesh:

Substances:

Year:  2014        PMID: 24929840     DOI: 10.1016/j.thromres.2014.05.034

Source DB:  PubMed          Journal:  Thromb Res        ISSN: 0049-3848            Impact factor:   3.944


  15 in total

1.  Cost-Effectiveness of Bridging Anticoagulation Among Patients with Nonvalvular Atrial Fibrillation.

Authors:  Matthew A Pappas; Geoffrey D Barnes; Sandeep Vijan
Journal:  J Gen Intern Med       Date:  2019-01-08       Impact factor: 5.128

2.  Underuse of Oral Anticoagulants and Inappropriate Prescription of Antiplatelet Therapy in Older Inpatients with Atrial Fibrillation.

Authors:  Lorette Averlant; Grégoire Ficheur; Laurie Ferret; Stéphane Boulé; François Puisieux; Michel Luyckx; Julien Soula; Alexandre Georges; Régis Beuscart; Emmanuel Chazard; Jean-Baptiste Beuscart
Journal:  Drugs Aging       Date:  2017-09       Impact factor: 3.923

3.  The changing characteristics of atrial fibrillation patients treated with warfarin.

Authors:  Andrew Putnam; Xiaokui Gu; Brian Haymart; Eva Kline-Rogers; Steve Almany; Jay Kozlowski; Gregory D Krol; Scott Kaatz; James B Froehlich; Geoffrey D Barnes
Journal:  J Thromb Thrombolysis       Date:  2015-11       Impact factor: 2.300

4.  Personalizing Bridging Anticoagulation in Patients with Nonvalvular Atrial Fibrillation-a Microsimulation Analysis.

Authors:  Matthew A Pappas; Geoffrey D Barnes; Sandeep Vijan
Journal:  J Gen Intern Med       Date:  2017-01-24       Impact factor: 5.128

5.  International Validity of the HOSPITAL Score to Predict 30-Day Potentially Avoidable Hospital Readmissions.

Authors:  Jacques D Donzé; Mark V Williams; Edmondo J Robinson; Eyal Zimlichman; Drahomir Aujesky; Eduard E Vasilevskis; Sunil Kripalani; Joshua P Metlay; Tamara Wallington; Grant S Fletcher; Andrew D Auerbach; Jeffrey L Schnipper
Journal:  JAMA Intern Med       Date:  2016-04       Impact factor: 21.873

6.  Structure and function of anticoagulation clinics in the United States: an AC forum membership survey.

Authors:  Geoffrey D Barnes; Eva Kline-Rogers; Christopher Graves; Eric Puroll; Xiaokui Gu; Kevin Townsend; Ellen McMahon; Terri Craig; James B Froehlich
Journal:  J Thromb Thrombolysis       Date:  2018-07       Impact factor: 2.300

7.  Predicting Thromboembolic and Bleeding Event Risk in Patients with Non-Valvular Atrial Fibrillation: A Systematic Review.

Authors:  Ethan D Borre; Adam Goode; Giselle Raitz; Bimal Shah; Angela Lowenstern; Ranee Chatterjee; Lauren Sharan; Nancy M Allen LaPointe; Roshini Yapa; J Kelly Davis; Kathryn Lallinger; Robyn Schmidt; Andrzej Kosinski; Sana M Al-Khatib; Gillian D Sanders
Journal:  Thromb Haemost       Date:  2018-10-30       Impact factor: 6.681

Review 8.  Direct Oral Anticoagulants for the Prevention of Stroke in Patients with Nonvalvular Atrial Fibrillation: Understanding Differences and Similarities.

Authors:  Paul P Dobesh; John Fanikos
Journal:  Drugs       Date:  2015-09       Impact factor: 9.546

9.  Multiple spontaneous hemorrhages after commencing warfarin therapy.

Authors:  Nobuhiro Akuzawa; Masahiko Kurabayashi
Journal:  SAGE Open Med Case Rep       Date:  2018-05-21

Review 10.  Predicting Atrial Fibrillation and Its Complications.

Authors:  Alvaro Alonso; Faye L Norby
Journal:  Circ J       Date:  2016-03-24       Impact factor: 2.993

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