OBJECTIVES: We assessed 5 risk stratification schemes for their ability to predict atrial fibrillation (AF)-related thromboembolism in a large community-based cohort. BACKGROUND: Risk schemes can help target anticoagulant therapy for patients at highest risk for AF-related thromboembolism. We tested the predictive ability of 5 risk schemes: the Atrial Fibrillation Investigators, Stroke Prevention in Atrial Fibrillation, CHADS(2) (Congestive heart failure, Hypertension, Age >or= 75 years, Diabetes mellitus, and prior Stroke or transient ischemic attack) index, Framingham score, and the 7th American College of Chest Physicians Guidelines. METHODS: We followed a cohort of 13,559 adults with AF for a median of 6.0 years. Among non-warfarin users, we identified incident thromboembolism (ischemic stroke or peripheral embolism) and risk factors from clinical databases. Each scheme was divided into low, intermediate, and high predicted risk categories and applied to the cohort. Annualized thromboembolism rates and c-statistics (to assess discrimination) were calculated for each risk scheme. RESULTS: We identified 685 validated thromboembolic events that occurred during 32,721 person-years off warfarin therapy. The risk schemes had only fair discriminating ability, with c-statistics ranging from 0.56 to 0.62. The proportion of patients assigned to individual risk categories varied widely across the schemes. The proportion categorized as low risk ranged from 11.7% to 37.1% across schemes, and the proportion considered high risk ranged from 16.4% to 80.4%. CONCLUSIONS: Current risk schemes have comparable, but only limited, overall ability to predict thromboembolism in persons with AF. Recommendations for antithrombotic therapy may vary widely depending on which scheme is applied for individual patients. Better risk stratification is crucially needed to improve selection of AF patients for anticoagulant therapy.
OBJECTIVES: We assessed 5 risk stratification schemes for their ability to predict atrial fibrillation (AF)-related thromboembolism in a large community-based cohort. BACKGROUND: Risk schemes can help target anticoagulant therapy for patients at highest risk for AF-related thromboembolism. We tested the predictive ability of 5 risk schemes: the Atrial Fibrillation Investigators, Stroke Prevention in Atrial Fibrillation, CHADS(2) (Congestive heart failure, Hypertension, Age >or= 75 years, Diabetes mellitus, and prior Stroke or transient ischemic attack) index, Framingham score, and the 7th American College of Chest Physicians Guidelines. METHODS: We followed a cohort of 13,559 adults with AF for a median of 6.0 years. Among non-warfarin users, we identified incident thromboembolism (ischemic stroke or peripheral embolism) and risk factors from clinical databases. Each scheme was divided into low, intermediate, and high predicted risk categories and applied to the cohort. Annualized thromboembolism rates and c-statistics (to assess discrimination) were calculated for each risk scheme. RESULTS: We identified 685 validated thromboembolic events that occurred during 32,721 person-years off warfarin therapy. The risk schemes had only fair discriminating ability, with c-statistics ranging from 0.56 to 0.62. The proportion of patients assigned to individual risk categories varied widely across the schemes. The proportion categorized as low risk ranged from 11.7% to 37.1% across schemes, and the proportion considered high risk ranged from 16.4% to 80.4%. CONCLUSIONS: Current risk schemes have comparable, but only limited, overall ability to predict thromboembolism in persons with AF. Recommendations for antithrombotic therapy may vary widely depending on which scheme is applied for individual patients. Better risk stratification is crucially needed to improve selection of AFpatients for anticoagulant therapy.
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