Literature DB >> 24009027

Development of a novel composite stroke and bleeding risk score in patients with atrial fibrillation: the AMADEUS Study.

Gregory Y H Lip1, Deirdre A Lane2, Harry Buller3, Stavros Apostolakis2.   

Abstract

BACKGROUND: The aim of the current analysis was to identify independent predictors of the overall clinical outcome of patients with atrial fibrillation (AF), including both stroke/thromboembolism and/or major bleeding. Given the overlap between stroke and bleeding risk factors, a composite risk-stratification score for stroke/thromboembolism or bleeding could potentially be developed.
METHODS: We used data from the vitamin K antagonist (VKA) arm (n = 2,293; 65% men; mean age 70 ± 9 years) of the AMADEUS (Evaluating the Use of SR34006 Compared to Warfarin or Acenocoumarol in Patients With Atrial Fibrillation) trial, which was a multicenter, randomized, open-label noninferiority study that compared fixed-dose idraparinux with VKA in patients with AF. We defined two composite end points: end point 1 was the combination of stroke/thromboembolism or major bleeding; end point 2 was defined as the combination of stroke, systemic or venous embolism, myocardial infarction, cardiovascular death, or major bleeding.
RESULTS: The independent predictors for composite end point 1 were age (P = .014), previous stroke/transient ischemic attack (P = .049), aspirin use (P = .002), and time in therapeutic range (P = .007). For composite end point 2, similar predictors were evident, plus left ventricular dysfunction (P = .011). Based on the regression models, two novel composite risk-prediction scores were developed and were validated externally in a "real-world" cohort of 441 outpatients with AF receiving anticoagulation treatment. Both composite scores 1 and 2 demonstrated numerically higher discriminatory performance (area under the curve [AUC], 0.728; 95% CI, 0.659-0.798 and AUC, 0.707; 95% CI, 0.655-0.758, for end points 1 and 2, respectively) and a positive net reclassification when compared with currently used risk models (CHADS2 [congestive heart failure, hypertension, age ≥ 75 years, diabetes, prior stroke or transient ischemic attack], CHA2DS2VASc [cardiac failure or dysfunction, hypertension, age ≥ 75 years [doubled], diabetes, stroke (doubled)-vascular disease, age 65 to 74 years, and sex category (female)], and HAS-BLED [hypertension, abnormal renal/liver function, stroke, bleeding history or predisposition, labile international normalized ratio, elderly, drugs/alcohol concomitantly]), but the differences were not statistically significant.
CONCLUSIONS: We have developed and validated two novel composite scores for stroke/thromboembolism/bleeding that offer good discriminatory and predictive performance. However, these composite risk scores did not perform better than the easier and more practical "traditional" stroke and bleeding risk scores that are currently in use, which allow greater practicality and a more personalized balancing of risks.

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Year:  2013        PMID: 24009027     DOI: 10.1378/chest.13-1635

Source DB:  PubMed          Journal:  Chest        ISSN: 0012-3692            Impact factor:   9.410


  9 in total

1.  Relation Classification for Bleeding Events From Electronic Health Records Using Deep Learning Systems: An Empirical Study.

Authors:  Avijit Mitra; Bhanu Pratap Singh Rawat; David D McManus; Hong Yu
Journal:  JMIR Med Inform       Date:  2021-07-02

Review 2.  Stroke And Bleeding Risk Assessment: Where Are We Now?

Authors:  Mikhail S Dzeshka; Gregory Y H Lip
Journal:  J Atr Fibrillation       Date:  2014-04-30

3.  Bleeding Entity Recognition in Electronic Health Records: A Comprehensive Analysis of End-to-End Systems.

Authors:  Avijit Mitra; Bhanu Pratap Singh Rawat; David McManus; Alok Kapoor; Hong Yu
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

4.  Haemorrhagic Transformation after Ischaemic Stroke in Patients Taking Non-vitamin K Antagonist Oral Anticoagulants.

Authors:  Jan C Purrucker; Kirsten Haas; Marcel Wolf; Timolaos Rizos; Shujah Khan; Peter Kraft; Sven Poli; Rainer Dziewas; Johannes Meyne; Frederick Palm; Sebastian Jander; Markus Möhlenbruch; Peter U Heuschmann; Roland Veltkamp
Journal:  J Stroke       Date:  2017-01-31       Impact factor: 6.967

5.  Effect of Standardized Warfarin Treatment Protocol on Anticoagulant Effect: Comparison of a Warfarin Medication Therapy Adherence Clinic with Usual Medical Care.

Authors:  Salihah Aidit; Yee Chang Soh; Chuan Seng Yap; Tahir M Khan; Chin Fen Neoh; Shazwani Shaharuddin; Yaman W Kassab; Rahul P Patel; Long C Ming
Journal:  Front Pharmacol       Date:  2017-11-09       Impact factor: 5.810

6.  Characteristics of Ischemic Versus Hemorrhagic Stroke in Patients Receiving Oral Anticoagulants: Results of the PASTA Study.

Authors:  Satoshi Suda; Arata Abe; Yasuyuki Iguchi; Yoshiki Yagita; Takao Kanzawa; Seiji Okubo; Nobuyuki Ohara; Takayuki Mizunari; Mineo Yamazaki; Nobuhito Nakajima; Kimito Kondo; Shigeru Fujimoto; Takeshi Inoue; Takeshi Iwanaga; Yuka Terasawa; Kensaku Shibazaki; Yu Kono; Makoto Nakajima; Masataka Nakajima; Masahiro Mishina; Koji Adachi; Ichiro Imafuku; Koichi Nomura; Takehiko Nagao; Hiroshi Yaguchi; Sadahisa Okamoto; Masato Osaki; Kazumi Kimura
Journal:  Intern Med       Date:  2021-09-04       Impact factor: 1.271

7.  Can We Predict Individual Combined Benefit and Harm of Therapy? Warfarin Therapy for Atrial Fibrillation as a Test Case.

Authors:  Guowei Li; Lehana Thabane; Thomas Delate; Daniel M Witt; Mitchell A H Levine; Ji Cheng; Anne Holbrook
Journal:  PLoS One       Date:  2016-08-11       Impact factor: 3.240

8.  The Joint Analysis of Multi-Omics Data Revealed the Methylation-Expression Regulations in Atrial Fibrillation.

Authors:  Ban Liu; Xin Shi; Keke Ding; Mengwei Lv; Yongjun Qian; Shijie Zhu; Changfa Guo; Yangyang Zhang
Journal:  Front Bioeng Biotechnol       Date:  2020-03-12

9.  Etiology of Ischemic Strokes of Patients with Atrial Fibrillation and Therapy with Anticoagulants.

Authors:  Jan C Purrucker; Kyra Hölscher; Jennifer Kollmer; Peter A Ringleb
Journal:  J Clin Med       Date:  2020-09-11       Impact factor: 4.241

  9 in total

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