title: How Well Do Stroke Risk Scores Predict Hemorrhage in Patients With Atrial Fibrillation?
abstract: The decision to use anticoagulants for atrial fibrillation depends on comparing a patient's estimated risk of stroke to their bleeding risk. Several of the risk factors in the stroke risk schemes overlap with hemorrhage risk. We compared how well 2 stroke risk scores (CHADS2 and CHA2DS2-VASc) and 2 hemorrhage risk scores (the ATRIA bleeding score and the HAS-BLED score) predicted major hemorrhage on and off warfarin in a cohort of 13,559 community-dwelling adults with AF. Over a cumulative 64,741 person-years of follow-up, we identified a total of 777 incident major hemorrhage events. The ATRIA bleeding score had the highest predictive ability of all the scores in patients on warfarin (c-index of 0.74 [0.72 to 0.76] compared with 0.65 [0.62 to 0.67] for CHADS2, 0.65 [0.62 to 0.67] for CHA2DS2-VASc, and 0.64 [0.61 to 0.66] for HAS-BLED) and in those off warfarin (0.77 [0.74 to 0.79] compared with 0.67 [0.64 to 0.71] for CHADS2, 0.67 [0.64 to 0.70] for CHA2DS2-VASc, and 0.68 [0.65 to 0.71] for HAS-BLED). In conclusion, although CHADS2 and CHA2DS2-VASc stroke scores were better at predicting hemorrhage than chance alone, they were inferior to the ATRIA bleeding score. Our study supports the use of dedicated hemorrhage risk stratification tools to predict major hemorrhage in atrial fibrillation.
authors.affiliation: Smith Center for Outcomes Research, Division of Cardiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
authors.forename: Gene R
authors.initials: GR
authors.lastname: Quinn
authors.affiliation: Clinical Epidemiology Unit, Massachusetts General Hospital, Boston, Massachusetts.
authors.forename: Daniel E
authors.initials: DE
authors.lastname: Singer
authors.affiliation: Clinical Epidemiology Unit, Massachusetts General Hospital, Boston, Massachusetts.
authors.forename: Yuchiao
authors.initials: Y
authors.lastname: Chang
authors.affiliation: Division of Research, Kaiser Permanente Northern California, Oakland, California; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California; Department of Medicine, University of California, San Francisco, San Francisco, California; Department of Health Research and Policy, Stanford University School of Medicine, Palo Alto, California.
authors.forename: Alan S
authors.initials: AS
authors.lastname: Go
authors.affiliation: Clinical Epidemiology Unit, Massachusetts General Hospital, Boston, Massachusetts.
authors.forename: Leila H
authors.initials: LH
authors.lastname: Borowsky
authors.affiliation: Department of Medicine, University of California, San Francisco, San Francisco, California; Division of Hospital Medicine, University of California, San Francisco, San Francisco, California. Electronic address: mfang@medicine.ucsf.edu.
authors.forename: Margaret C
authors.initials: MC
authors.lastname: Fang
mesh_terms: D000368:Aged; D000925:Anticoagulants / Q000008:administration & dosage* / Q000009:adverse effects; D001281:Atrial Fibrillation / Q000150:complications / Q000175:diagnosis / Q000188:drug therapy*; D015331:Cohort Studies; D005260:Female; D005500:Follow-Up Studies; D006470:Hemorrhage / Q000139:chemically induced*; D006801:Humans; D019934:International Normalized Ratio / Q000379:methods; D008297:Male; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012307:Risk Factors; D020521:Stroke / Q000209:etiology* / Q000517:prevention & control*; D014859:Warfarin / Q000008:administration & dosage* / Q000009:adverse effects
chemical_list: D000925:Anticoagulants; D014859:Warfarin