Abstract
Introduction: Anticoagulation reduces stroke risk in atrial fibrillation (AF) but increases bleeding. Risk calculators are used to inform decision making for anticoagulation in AF. Yet, existing tools have substantial limitations and improvement efforts failed to change practice. Hypotheses: Biomarkers of ischemic stroke risk for general populations are associated with stroke risk in AF and improve performance of a recommended risk score (CHA 2 DS 2 -VASc). Methods: REGARDS is a prospective cohort of 30,239 Black or White adults aged ≥45 monitored for stroke. Nine blood biomarkers were measured at baseline in participants with AF, no prior stroke, and not taking anticoagulation at baseline. Hazard ratios of ischemic stroke were estimated by Cox models adjusted for demographics and stroke risk factors. Models with CHA 2 DS 2 -VASc alone and with biomarkers (CHA 2 DS 2 -VASc-B) were compared using tests of fit (likelihood ratio test and Aikake information criterion [AIC]) and predictive ability (continuous net reclassification index [NRI]). Results: Among 2,411 participants with baseline AF (median age 69, 55% female, 36% Black), 163 (7%) developed stroke over 13 years. After adjustments, higher cystatin C, growth differentiation factor 15 (GDF-15), interleukin 6, lipoprotein (a), and N-terminal pro-B type natriuretic peptide (NTproBNP) were associated with higher stroke risk (Figure A). Including all biomarkers substantially improved CHA 2 DS 2 -VASc model fit (Figure B; p <0.001; ΔAIC -12.6; <-10 indicates marked improvement) and predictive ability (Figure C; 5-year NRI 0.42). Adding only GDF-15 and NTproBNP resulted in the best model fit and a similar NRI, compared to all biomarkers. Conclusions: Higher levels of five blood biomarkers were associated with ischemic stroke risk in a large general population cohort with AF. Moreover, the CHA 2 DS 2 -VASc-B model was superior to CHA 2 DS 2 -VASc. Findings suggest we can better tailor anticoagulation to reduce stroke in AF.
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