Please use this identifier to cite or link to this item: http://ahro.austin.org.au/austinjspui/handle/1/18624
Title: Predictors for atrial fibrillation detection after cryptogenic stroke: Results from CRYSTAL AF.
Authors: Thijs, Vincent N;Brachmann, Johannes;Morillo, Carlos A;Passman, Rod S;Sanna, Tommaso;Bernstein, Richard A;Diener, Hans-Christoph;Di Lazzaro, Vincenzo;Rymer, Marilyn M;Hogge, Laurence;Rogers, Tyson B;Ziegler, Paul D;Assar, Manish D
Affiliation: Baylor University Medical Center, Dallas, TX
Department of Neurology, Austin Health, Heidelberg, Victoria, Australia
The Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia
Medtronic, Maastricht, Netherlands
Medtronic, Mounds View, Minneapolis, MN
Hospital Klinikum Coburg, Teaching Hospital of the University of Würzburg, Coburg, Germany
Population Health Research Institute, McMaster University, Hamilton, Canada
Northwestern University Feinberg School of Medicine, Chicago, IL, USA
Institute of Cardiology, Catholic University of the Sacred Heart, Rome, Italy
Davee Department of Neurology, Northwestern University, Chicago, IL, USA
Department of Neurology, University Hospital Essen University Duisburg-Essen, Germany
Institute of Neurology, University Campus Bio-Medico of Rome, Rome, Italy
University of Kansas Medical Center, Kansas City, USA
Issue Date: 19-Jan-2016
EDate: 2015-12-18
Citation: Neurology 2016; 86(3): 261-9
Abstract: We assessed predictors of atrial fibrillation (AF) in cryptogenic stroke (CS) or transient ischemic attack (TIA) patients who received an insertable cardiac monitor (ICM). We studied patients with CS/TIA who were randomized to ICM within the CRYSTAL AF study. We assessed whether age, sex, race, body mass index, type and severity of index ischemic event, CHADS2 score, PR interval, and presence of diabetes, hypertension, congestive heart failure, or patent foramen ovale and premature atrial contractions predicted AF development within the initial 12 and 36 months of follow-up using Cox proportional hazards models. Among 221 patients randomized to ICM (age 61.6 ± 11.4 years, 64% male), AF episodes were detected in 29 patients within 12 months and 42 patients at 36 months. Significant univariate predictors of AF at 12 months included age (hazard ratio [HR] per decade 2.0 [95% confidence interval 1.4-2.8], p = 0.002), CHADS2 score (HR 1.9 per one point [1.3-2.8], p = 0.008), PR interval (HR 1.3 per 10 milliseconds [1.2-1.4], p < 0.0001), premature atrial contractions (HR 3.9 for >123 vs 0 [1.3-12.0], p = 0.009 across quartiles), and diabetes (HR 2.3 [1.0-5.2], p < 0.05). In multivariate analysis, age (HR per decade 1.9 [1.3-2.8], p = 0.0009) and PR interval (HR 1.3 [1.2-1.4], p < 0.0001) remained significant and together yielded an area under the receiver operating characteristic curve of 0.78 (0.70-0.85). The same predictors were found at 36 months. Increasing age and a prolonged PR interval at enrollment were independently associated with an increased AF incidence in CS patients. However, they offered only moderate predictive ability in determining which CS patients had AF detected by the ICM.
URI: http://ahro.austin.org.au/austinjspui/handle/1/18624
DOI: 10.1212/WNL.0000000000002282
ORCID: 0000-0002-6614-8417
PubMed URL: 26683642
Type: Journal Article
Research Support, Non-U.S. Gov't
Appears in Collections:Journal articles

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