Thromb Haemost 2018; 118(12): 2171-2187
DOI: 10.1055/s-0038-1675400
Stroke, Systemic or Venous Thromboembolism
Georg Thieme Verlag KG Stuttgart · New York

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

Ethan D. Borre
1  Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
,
Adam Goode
1  Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
2  Department of Orthopedic Surgery, Duke University School of Medicine, Durham, North Carolina, United States
,
Giselle Raitz
1  Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
,
Bimal Shah
1  Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
3  Livongo, Mountain View, California, United States
,
Angela Lowenstern
4  Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
5  Division of Cardiology, Duke University School of Medicine, Durham, North Carolina
,
Ranee Chatterjee
1  Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
,
Lauren Sharan
1  Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
,
Nancy M. Allen LaPointe
1  Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
6  Premier Inc., Charlotte, North Carolina, United States
,
Roshini Yapa
7  Department of Medicine, University of Colorado, Aurora, Colorado, United States
,
J. Kelly Davis
8  Duke-Margolis Center for Health Policy, Duke University, Durham, North Carolina, United States
,
Kathryn Lallinger
1  Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
4  Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
9  Evidence-Based Practice Center, Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
,
Robyn Schmidt
1  Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
4  Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
9  Evidence-Based Practice Center, Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
,
Andrzej Kosinski
10  Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, United States
,
Sana M. Al-Khatib
4  Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
5  Division of Cardiology, Duke University School of Medicine, Durham, North Carolina
,
Gillian D. Sanders
1  Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States
4  Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
8  Duke-Margolis Center for Health Policy, Duke University, Durham, North Carolina, United States
9  Evidence-Based Practice Center, Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States
› Author Affiliations
Funding This project was funded under Contract No. 290–2015–00004-I from the Agency for Healthcare Research and Quality (AHRQ), U.S. Department of Health and Human Services. The authors of this manuscript are responsible for its content. Statements in the manuscript should not be construed as endorsement by the Patient-Centered Outcomes Research Institute (PCORI), AHRQ and the U.S. Department of Health and Human Services. AHRQ retains a license to display, reproduce and distribute the data and the report from which this manuscript was derived under the terms of the agency's contract with the author.
Further Information

Publication History

10 September 2018

27 September 2018

Publication Date:
30 October 2018 (eFirst)

Abstract

Background Atrial fibrillation (AF) is a common cardiac arrhythmia that increases the risk of stroke. Medical therapy for decreasing stroke risk involves anticoagulation, which may increase bleeding risk for certain patients. In determining the optimal therapy for stroke prevention for patients with AF, clinicians use tools with various clinical, imaging and patient characteristics to weigh stroke risk against therapy-associated bleeding risk.

Aim This article reviews published literature and summarizes available risk stratification tools for stroke and bleeding prediction in patients with AF.

Methods We searched for English-language studies in PubMed, Embase and the Cochrane Database of Systematic Reviews published between 1 January 2000 and 14 February 2018. Two reviewers screened citations for studies that examined tools for predicting thromboembolic and bleeding risks in patients with AF. Data regarding study design, patient characteristics, interventions, outcomes, quality, and applicability were extracted.

Results Sixty-one studies were relevant to predicting thromboembolic risk and 38 to predicting bleeding risk. Data suggest that CHADS2, CHA2DS2-VASc and the age, biomarkers, and clinical history (ABC) risk scores have the best evidence for predicting thromboembolic risk (moderate strength of evidence for limited prediction ability of each score) and that HAS-BLED has the best evidence for predicting bleeding risk (moderate strength of evidence).

Limitations Studies were heterogeneous in methodology and populations of interest, setting, interventions and outcomes analysed.

Conclusion CHADS2, CHA2DS2-VASc and ABC scores have the best prediction for stroke events, and HAS-BLED provides the best prediction for bleeding risk. Future studies should define the role of imaging tools and biomarkers in enhancing the accuracy of risk prediction tools.

Primary Funding Source Patient-Centered Outcomes Research Institute (PROSPERO #CRD42017069999)

Supplementary Material