Refining Stroke Prediction in Atrial Fibrillation Patients by Addition of African-American Ethnicity to CHA2DS2-VASc Score

BACKGROUND Prior studies show that African-American patients have a higher risk of stroke compared with Caucasians. OBJECTIVES This study hypothesized addition of African-American ethnicity to CHA(2)DS(2)-VASc (congestive heart failure, hypertension, age >= 75 years, diabetes, previous stroke, vascular disease, age 65 to 74, and female sex) score might improve stroke prediction in patients with atrial fibrillation (AF). METHODS Medicare claims from January 2010 to December 2012 identified patients with newly diagnosed AF. The CHA(2)DS(2)-VASc was calculated on the basis of diagnoses in claims incurred during 12 months before first AF diagnosis. Ethnicity was identified from the Beneficiary Summary File. CHA(2)DS(2)-VASc-R score was calculated by giving 1 additional point for African-American ethnicity. The primary outcome was stroke, defined by primary diagnosis on acute inpatient admissions after the initial AF diagnosis. We used proportional hazards regression to determine the relationship between stroke and the CHA(2)DS(2)-VASc or a revised CHA(2)DS(2)-VASc-R score. RESULTS Of 460,417 patients with AF, 390,590 (85%) were non-Hispanic whites, 31,702 (7%) were non-Hispanic African Americans, and the remainder were other non-white ethnicities. Mean age was 79.2 +/- 8.0 years, with 60% females. Overall, 16,703 stroke events occurred, and 151,441 (32.7%) patients died during a mean follow-up period of 18.0 months. Compared with CHA(2)DS(2)-VASc, CHA(2)DS(2)-VASc-R score improved the fit of the model significantly as measured by the log likelihood ratio statistic (p < 0.001). Among individual risk factors in CHA(2)DS(2)-VASc-R score, only prior stroke, age >= 75 years, and female sex had a stronger association with incident stroke than African-American ethnicity. CONCLUSIONS In patients >65 years of age with newly diagnosed AF, the addition of ethnicity to CHA(2)DS(2)-VASc score significantly improved stroke prediction. (C) 2016 by the American College of Cardiology Foundation.