Real world effectiveness of warfarin among ischemic stroke patients with atrial fibrillation: observational analysis from Patient-Centered Research into Outcomes Stroke Patients Prefer and Effectiveness Research (PROSPER) study.
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To examine the association between warfarin treatment and longitudinal outcomes after ischemic stroke in patients with atrial fibrillation in community practice.Observational study.Hospitals (n = 1487) participating in the Get With The Guidelines (GWTG)-Stroke program in the United States, from 2009 to 2011.12,552 warfarin naive atrial fibrillation patients admitted to hospital for ischemic stroke and treated with warfarin compared with no oral anticoagulant at discharge, linked to Medicare claims for longitudinal outcomes.Major adverse cardiovascular events (MACE) and home time, a patient centered outcomes measure defined as the total number of days free from institutional care after discharge. A propensity score inverse probability weighting method was used to account for all differences in observed characteristics between treatment groups.Among 12,552 survivors of stroke, 11,039 (88%) were treated with warfarin at discharge. Warfarin treated patients were slightly younger and less likely to have a history of previous stroke or coronary artery disease but had similar severity of stroke as measured by the National Institutes of Health Stroke Scale. Relative to those not treated, patients treated with warfarin had more days at home (as opposed to institutional care) during the two years after discharge (adjusted home time difference 47.6 days, 99% confidence interval 26.9 to 68.2). Patients discharged on warfarin treatment also had a reduced risk of MACE (adjusted hazard ratio 0.87, 99% confidence interval 0.78 to 0.98), all cause mortality (0.72, 0.63 to 0.84), and recurrent ischemic stroke (0.63, 0.48 to 0.83). These differences were consistent among clinically relevant subgroups by age, sex, stroke severity, and history of previous coronary artery disease and stroke.Among ischemic stroke patients with atrial fibrillation, warfarin treatment was associated with improved long term clinical outcomes and more days at home. Clinical trial registration Clinical trials NCT02146274.
Published Version (Please cite this version)
Xian, Ying, Jingjing Wu, Emily C O'Brien, Gregg C Fonarow, DaiWai M Olson, Lee H Schwamm, Deepak L Bhatt, Eric E Smith, et al. (2015). Real world effectiveness of warfarin among ischemic stroke patients with atrial fibrillation: observational analysis from Patient-Centered Research into Outcomes Stroke Patients Prefer and Effectiveness Research (PROSPER) study. BMJ (Clinical research ed.), 351. p. h3786. 10.1136/bmj.h3786 Retrieved from https://hdl.handle.net/10161/21677.
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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, 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, and builds upon Duke’s national leadership in trustworthy 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-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). He spearheads Duke’s role as a founding partner of the Coalition for Health AI (CHAI) 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.
Dr. Pencina is an internationally recognized authority in the evaluation of AI tools and algorithms. Guideline groups rely on his work to advance best practices for the application of algorithms in clinical medicine. He is actively involved in the design, conduct, and analysis of clinical studies with a focus on novel and efficient designs and applications of machine learning for medical decision support. He interacts frequently with investigators from academic and industry institutions as well as regulatory officials from the U.S. Food and Drug Administration.
Widely noted as an expert on risk prediction models, Dr. Pencina has authored or co-authored 400 peer-reviewed publications that have been cited over 111,000 times. Thomson Reuters/Clarivate Analytics has recognized him as a “highly cited researcher” in clinical medicine from 2014-2021 and social sciences from 2014-2022. He serves as deputy editor for statistics at JAMA-Cardiology and associate editor for Statistics in Medicine.
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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