Association of Preceding Antithrombotic Treatment With Acute Ischemic Stroke Severity and In-Hospital Outcomes Among Patients With Atrial Fibrillation.


Importance:Antithrombotic therapies are known to prevent stroke for patients with atrial fibrillation (AF) but are often underused in community practice. Objectives:To examine the prevalence of patients with acute ischemic stroke with known history of AF who were not receiving guideline-recommended antithrombotic treatment before stroke and to determine the association of preceding antithrombotic therapy with stroke severity and in-hospital outcomes. Design, Setting, and Participants:Retrospective observational study of 94 474 patients with acute ischemic stroke and known history of AF admitted from October 2012 through March 2015 to 1622 hospitals participating in the Get With the Guidelines-Stroke program. Exposures:Antithrombotic therapy before stroke. Main Outcomes and Measures:Stroke severity as measured by the National Institutes of Health Stroke Scale (NIHSS; range of 0-42, with a higher score indicating greater stroke severity and a score ≥16 indicating moderate or severe stroke), and in-hospital mortality. Results:Of 94 474 patients (mean [SD] age, 79.9 [11.0] years; 57.0% women), 7176 (7.6%) were receiving therapeutic warfarin (international normalized ratio [INR] ≥2) and 8290 (8.8%) were receiving non-vitamin K antagonist oral anticoagulants (NOACs) preceding the stroke. A total of 79 008 patients (83.6%) were not receiving therapeutic anticoagulation; 12 751 (13.5%) had subtherapeutic warfarin anticoagulation (INR <2) at the time of stroke, 37 674 (39.9%) were receiving antiplatelet therapy only, and 28 583 (30.3%) were not receiving any antithrombotic treatment. Among 91 155 high-risk patients (prestroke CHA2DS2-VASc score ≥2), 76 071 (83.5%) were not receiving therapeutic warfarin or NOACs before stroke. The unadjusted rates of moderate or severe stroke were lower among patients receiving therapeutic warfarin (15.8% [95% CI, 14.8%-16.7%]) and NOACs (17.5% [95% CI, 16.6%-18.4%]) than among those receiving no antithrombotic therapy (27.1% [95% CI, 26.6%-27.7%]), antiplatelet therapy only (24.8% [95% CI, 24.3%-25.3%]), or subtherapeutic warfarin (25.8% [95% CI, 25.0%-26.6%]); unadjusted rates of in-hospital mortality also were lower for those receiving therapeutic warfarin (6.4% [95% CI, 5.8%-7.0%]) and NOACs (6.3% [95% CI, 5.7%-6.8%]) compared with those receiving no antithrombotic therapy (9.3% [95% CI, 8.9%-9.6%]), antiplatelet therapy only (8.1% [95% CI, 7.8%-8.3%]), or subtherapeutic warfarin (8.8% [95% CI, 8.3%-9.3%]). After adjusting for potential confounders, compared with no antithrombotic treatment, preceding use of therapeutic warfarin, NOACs, or antiplatelet therapy was associated with lower odds of moderate or severe stroke (adjusted odds ratio [95% CI], 0.56 [0.51-0.60], 0.65 [0.61-0.71], and 0.88 [0.84-0.92], respectively) and in-hospital mortality (adjusted odds ratio [95% CI], 0.75 [0.67-0.85], 0.79 [0.72-0.88], and 0.83 [0.78-0.88], respectively). Conclusions and Relevance:Among patients with atrial fibrillation who had experienced an acute ischemic stroke, inadequate therapeutic anticoagulation preceding the stroke was prevalent. Therapeutic anticoagulation was associated with lower odds of moderate or severe stroke and lower odds of in-hospital mortality.





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Publication Info

Xian, Ying, Emily C O'Brien, Li Liang, Haolin Xu, Lee H Schwamm, Gregg C Fonarow, Deepak L Bhatt, Eric E Smith, et al. (2017). Association of Preceding Antithrombotic Treatment With Acute Ischemic Stroke Severity and In-Hospital Outcomes Among Patients With Atrial Fibrillation. JAMA, 317(10). pp. 1057–1067. 10.1001/jama.2017.1371 Retrieved from

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Ying Xian

Adjunct Associate Professor in the Department of Neurology

Emily O'Brien

Associate Professor in Population Health Sciences

Dr. Emily O’Brien is Associate Professor in Population Health Sciences, Associate Professor in Neurology, Core Faculty Member at Duke-Margolis Center for Health Policy,  and Co-Director of Population Health Sciences at the Duke Clinical Research Institute. Her research focuses on comparative effectiveness, patient-centered outcomes, and pragmatic health systems research in cardiovascular and pulmonary disease. Her areas of expertise include: Epidemiology, Pragmatic Clinical Trials, and Clinical Decision Sciences. Dr. O’Brien received her PhD in Epidemiology from the University of North Carolina in Chapel Hill. As principal investigator for projects funded by the FDA, NIH, and PCORI, she has extensive experience working with diverse data sources including registries, epidemiologic cohorts, electronic health records, and administrative claims data. Dr. O’Brien teaches Analytic Methods in the Department of Population Health Sciences PhD program and has co-authored over 160 manuscripts in peer-reviewed journals on topics ranging from epidemiologic methods, comparative effectiveness, and pragmatic clinical trials. She is an associate editor for Circulation: Cardiovascular Quality and Outcomes, Chair of the AHA QCOR Scientific & Clinical Education Lifelong Learning Committee, social media editor for the Journal of the American Heart Association, and a fellow of the American Heart Association.

Haolin Xu

Biostatistician, Senior

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 fields of data science, health care, and AI, contributing to Duke’s national leadership in trustworthy health AI.

Dr. Pencina partners with key leaders to develop data science strategies for Duke Health that span and connect academic research and clinical care. As vice dean for data science, he develops and implements quantitative science strategies to support the School of Medicine’s missions in education and training, laboratory and clinical science, and data science.

He co-founded and co-leads the national Coalition for Health AI (CHAI), a multi-stakeholder effort whose mission is to increase trustworthiness of AI by developing guidelines to drive high-quality health care through the adoption of credible, fair, and transparent health AI systems. He also spearheaded the establishment and co-chairs Duke Health’s Algorithm-Based Clinical Decision Support (ABCDS) Oversight Committee and serves as co-director of Duke’s Collaborative to Advance Clinical Health Equity (CACHE).

Dr. Pencina is an internationally recognized authority in the evaluation of AI algorithms. Guideline groups rely on his work to advance best practices for the application of clinical decision support tools in health delivery. He interacts frequently with investigators from academic and industry institutions as well as government officials. Since 2014, he has been acknowledged annually by Thomson Reuters/Clarivate Analytics as one of the world’s "highly cited researchers" in clinical medicine and social sciences, with over 400 publications cited over 100,000 times. He serves as a deputy editor for statistics at JAMA-Cardiology.

Dr. Pencina joined the Duke University faculty in 2013, and served as director of biostatistics for the Duke Clinical Research Institute until 2018. Previously, he was an associate professor in the Department of Biostatistics at Boston University and the Framingham Heart Study, and director of statistical consulting at the Harvard Clinical Research Institute. He received his PhD in Mathematics and Statistics from Boston University in 2003 and holds master’s degrees from the University of Warsaw in actuarial mathematics and business culture.


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Adrian Felipe Hernandez

Duke Health Cardiology Professor

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