The ORBIT bleeding score: a simple bedside score to assess bleeding risk in atrial fibrillation.
Abstract
BACKGROUND: Therapeutic decisions in atrial fibrillation (AF) are often influenced
by assessment of bleeding risk. However, existing bleeding risk scores have limitations.
OBJECTIVES: We sought to develop and validate a novel bleeding risk score using routinely
available clinical information to predict major bleeding in a large, community-based
AF population. METHODS: We analysed data from Outcomes Registry for Better Informed
Treatment of Atrial Fibrillation (ORBIT-AF), a prospective registry that enrolled
incident and prevalent AF patients at 176 US sites. Using Cox proportional hazards
regression, we identified factors independently associated with major bleeding among
patients taking oral anticoagulation (OAC) over a median follow-up of 2 years (interquartile
range = 1.6-2.5). We also created a numerical bedside risk score that included the
five most predictive risk factors weighted according to their strength of association
with major bleeding. The predictive performance of the full model, the simple five-item
score, and two existing risk scores (hypertension, abnormal renal/liver function,
stroke, bleeding history or predisposition, labile INR, elderly, drugs/alcohol concomitantly,
HAS-BLED, and anticoagulation and risk factors in atrial fibrillation, ATRIA) were
then assessed in both the ORBIT-AF cohort and a separate clinical trial population,
Rivaroxaban Once-daily oral direct factor Xa inhibition compared with vitamin K antagonism
for prevention of stroke and embolism trial in atrial fibrillation (ROCKET-AF). RESULTS:
Among 7411 ORBIT-AF patients taking OAC, the rate of major bleeding was 4.0/100 person-years.
The full continuous model (12 variables) and five-factor ORBIT risk score (older age
[75+ years], reduced haemoglobin/haematocrit/history of anaemia, bleeding history,
insufficient kidney function, and treatment with antiplatelet) both had good ability
to identify those who bled vs. not (C-index 0.69 and 0.67, respectively). These scores
both had similar discrimination, but markedly better calibration when compared with
the HAS-BLED and ATRIA scores in an external validation population from the ROCKET-AF
trial. CONCLUSIONS: The five-element ORBIT bleeding risk score had better ability
to predict major bleeding in AF patients when compared with HAS-BLED and ATRIA risk
scores. The ORBIT risk score can provide a simple, easily remembered tool to support
clinical decision making.
Type
Journal articleSubject
AnticoagulantsAtrial fibrillation
Major bleeding
Risk prediction
Aged
Aged, 80 and over
Anticoagulants
Atrial Fibrillation
Female
Hemorrhage
Humans
Male
Middle Aged
Point-of-Care Systems
Prospective Studies
Registries
Risk Assessment
Risk Factors
Stroke
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https://hdl.handle.net/10161/15004Published Version (Please cite this version)
10.1093/eurheartj/ehv476Publication Info
O'Brien, Emily C; Simon, DaJuanicia N; Thomas, Laine E; Hylek, Elaine M; Gersh, Bernard
J; Ansell, Jack E; ... Peterson, Eric D (2015). The ORBIT bleeding score: a simple bedside score to assess bleeding risk in atrial
fibrillation. Eur Heart J, 36(46). pp. 3258-3264. 10.1093/eurheartj/ehv476. Retrieved from https://hdl.handle.net/10161/15004.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Emily O'Brien
Associate Professor in Population Health Sciences
I am an epidemiologist and health services researcher at the Duke Clinical Research
Institute. My research focuses on comparative effectiveness, patient-centered outcomes,
and pragmatic health services research in cardiovascular and pulmonary disease.Areas
of expertise: Epidemiology, Health Services Research, and Clinical Decision Sciences
Michael J Pencina
Professor of Biostatistics & Bioinformatics
Michael J. Pencina, PhD Chief Data Scientist, Duke Health Vice Dean for Data Science
Director, Duke AI Health Professor, Biostatistics & Bioinformatics Duke University
School of Medicine
Michael J. Pencina, PhD, is Duke Health's chief data scientist and serves as vice
dean for data science, director of Duke AI Health, and professor of biostatistics
and bioinformatics at the Duke University School of Medicine. His work bridges the
fiel
Eric David Peterson
Fred Cobb, M.D. Distinguished Professor of Medicine
Dr Peterson is the Fred Cobb Distinguished Professor of Medicine in the Division of
Cardiology, a DukeMed Scholar, and the Past Executive Director of the Duke Clinical
Research Institute (DCRI), Durham, NC, USA.
Dr Peterson is the Principal Investigator of the National Institute of Health, Lung
and Blood Institute (NHLBI) Spironolactone Initiation Registry Randomized Interventional
Trial in Heart Failure With Preserved Ejection Fraction (SPIRRIT) Trial He is also
the Principal I
This author no longer has a Scholars@Duke profile, so the information shown here reflects
their Duke status at the time this item was deposited.
Jonathan Paul Piccini Sr.
Professor of Medicine
Jonathan P. Piccini, MD, MHS, FACC, FAHA, FHRS is a clinical cardiac electrophysiologist
and Associate Professor of Medicine with Tenure at Duke University Medical Center
and the Duke Clinical Research Institute. He is the Director of the Cardiac Electrophysiology
section at the Duke Heart Center. His focus is on the care of patients with atrial
fibrillation and complex arrhythmias, with particular emphasis on catheter ablation,
left atrial appendage occlusion, and lead extraction. His resear
Laine Elliott Thomas
Professor of Biostatistics & Bioinformatics
As Deputy Director, Laine Thomas, PhD provides complementary leadership in strategy
and development of the group and DCRI. She has an outstanding record of scientific
and strategic collaboration, independent research, leadership and mentoring well known
to her colleagues at the DCRI.
Thomas joined the DCRI in 2009. She serves as Associate Director for Biostatistics
at DCRI and Associate Chair for Equity, Diversity and Inclusion within the Department
of
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