Literature DB >> 26482233

Evaluation of the HAS-BLED, ATRIA, and ORBIT Bleeding Risk Scores in Patients with Atrial Fibrillation Taking Warfarin.

Keitaro Senoo1, Marco Proietti1, Deirdre A Lane1, Gregory Y H Lip2.   

Abstract

OBJECTIVES: Various bleeding risk prediction schemes, such as the Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized Ratio, Elderly, Drugs/alcohol (HAS-BLED), Anticoagulation and Risk Factors in Atrial Fibrillation (ATRIA), and Outcomes Registry for Better Informed Treatment (ORBIT) scores, have been proposed in patients with atrial fibrillation. We compared the relative predictive values of these bleeding risk scores for clinically relevant bleeding and the relationship of ATRIA and ORBIT scores to the quality of anticoagulation control on warfarin, as reflected by time in therapeutic range.
METHODS: We conducted a post hoc ancillary analysis of clinically relevant bleeding and major bleeding events among 2293 patients receiving warfarin therapy in the AMADEUS trial.
RESULTS: Only HAS-BLED was significantly predictive for clinically relevant bleeding, and all 3 risk scores were predictive for major bleeding. The predictive performance of HAS-BLED was modest, as reflected by c-indexes of 0.59 (P < .001) and 0.65 (P < .002) for clinically relevant bleeding and major bleeding, respectively. The HAS-BLED score performed better than the ATRIA (P = .002) or ORBIT (P = .001) score in predicting any clinically relevant bleeding. Only the HAS-BLED score was significantly associated with the risk for both bleeding outcomes on Cox regression analysis (any clinically relevant bleeding: hazard ratio, 1.85; 95% confidence interval, 1.43-2.40, P < .001; major bleeding: hazard ratio, 2.40; 95% confidence interval, 1.28-4.52; P = .007). There were strong inverse correlations of ATRIA and ORBIT scores to time in therapeutic range as a continuous variable (low risk ATRIA, r = -0.96; P = .003; ORBIT, r = -0.96; P = .003). Improvement in the predictive performance for both ATRIA and ORBIT scores for any clinically relevant bleeding was achieved by adding time in therapeutic range to both scores, with significant differences in c-indexes (P = .001 and P = .002, respectively), net reclassification improvement, and integrated discriminant improvement (both P < .001).
CONCLUSIONS: All 3 bleeding risk prediction scores demonstrated modest predictive ability for bleeding outcomes, although the HAS-BLED score performed better than the ATRIA or ORBIT score. Significant improvements in both ATRIA and ORBIT score prediction performances were achieved by adding time in therapeutic range to both scores.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  ATRIA; Anticoagulation; Bleeding; HAS-BLED; ORBIT; Risk assessment

Mesh:

Substances:

Year:  2015        PMID: 26482233     DOI: 10.1016/j.amjmed.2015.10.001

Source DB:  PubMed          Journal:  Am J Med        ISSN: 0002-9343            Impact factor:   4.965


  20 in total

1.  Combination of Oral Anticoagulants and Single Antiplatelets versus Triple Therapy in Nonvalvular Atrial Fibrillation and Acute Coronary Syndrome: Stroke Prevention among Asians.

Authors:  Anwar Santoso; Sunu B Raharjo
Journal:  Int J Angiol       Date:  2020-05-06

2.  Guideline-concordant initiation of oral anticoagulant therapy for stroke prevention in older veterans with atrial fibrillation eligible for Medicare Part D.

Authors:  Nicolae Done; Amanda M Roy; Yingzhe Yuan; Steven D Pizer; Adam J Rose; Julia C Prentice
Journal:  Health Serv Res       Date:  2018-11-11       Impact factor: 3.402

3.  Atrial fibrillation: NICE 2021 update and the focus on anticoagulation.

Authors:  Nicholas R Jones; Thomas Round; Kim Rajappan
Journal:  Br J Gen Pract       Date:  2022-03-31       Impact factor: 5.386

4.  Influence of Age on Warfarin Dose, Anticoagulation Control, and Risk of Hemorrhage.

Authors:  Aditi Shendre; Gaurav M Parmar; Chrisly Dillon; Timothy Mark Beasley; Nita A Limdi
Journal:  Pharmacotherapy       Date:  2018-02-27       Impact factor: 4.705

5.  Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment.

Authors:  Jeph Herrin; Neena S Abraham; Xiaoxi Yao; Peter A Noseworthy; Jonathan Inselman; Nilay D Shah; Che Ngufor
Journal:  JAMA Netw Open       Date:  2021-05-03

6.  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

7.  Assessing bleeding risk in 4824 Asian patients with atrial fibrillation: The Beijing PLA Hospital Atrial Fibrillation Project.

Authors:  Yu-Tao Guo; Ye Zhang; Xiang-Min Shi; Zhao-Liang Shan; Chun-Jiang Wang; Yu-Tang Wang; Yun-Dai Chen; Gregory Y H Lip
Journal:  Sci Rep       Date:  2016-08-25       Impact factor: 4.379

8.  Risks of postextraction bleeding after receiving direct oral anticoagulants or warfarin: a retrospective cohort study.

Authors:  Takahiro Yagyuu; Mao Kawakami; Yoshihiro Ueyama; Mitsuhiko Imada; Miyako Kurihara; Yumiko Matsusue; Yuichiro Imai; Kazuhiko Yamamoto; Tadaaki Kirita
Journal:  BMJ Open       Date:  2017-08-21       Impact factor: 2.692

Review 9.  Predicting Atrial Fibrillation and Its Complications.

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

10.  Major Bleeding in Patients with Non-Valvular Atrial Fibrillation: Impact of Time in Therapeutic Range on Contemporary Bleeding Risk Scores.

Authors:  Marco Proietti; Keitaro Senoo; Deirdre A Lane; Gregory Y H Lip
Journal:  Sci Rep       Date:  2016-04-12       Impact factor: 4.379

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