Research from JAMA — Validation of Clinical Classification Schemes for Predicting Stroke — Results From the National Registry of Atrial Fibrillation — ContextPatients who have atrial fibrillation (AF) have an increased risk of stroke, but their absolute rate of stroke depends on age and comorbid conditions.ObjectiveTo assess the predictive value of classification schemes that estimate stroke risk in patients with AF.Design, Setting, and PatientsTwo existing classification schemes were combined into a new stroke-risk scheme, the CHADS2 index, and all 3 classification schemes were validated. The CHADS2 was formed by assigning 1 point each for the presence of congestive heart failure, hypertension, age 75 years or older, and diabetes mellitus and by assigning 2 points for history of stroke or transient ischemic attack. Data from peer review organizations representing 7 states were used to assemble a National Registry of AF (NRAF) consisting of 1733 Medicare beneficiaries aged 65 to 95 years who had nonrheumatic AF and were not prescribed warfarin at hospital discharge.Main Outcome MeasureHospitalization for ischemic stroke, determined by Medicare claims data.ResultsDuring 2121 patient-years of follow-up, 94 patients were readmitted to the hospital for ischemic stroke (stroke rate, 4.4 per 100 patient-years). As indicated by a c statistic greater than 0.5, the 2 existing classification schemes predicted stroke better than chance: c of 0.68 (95% confidence interval [CI], 0.65-0.71) for the scheme developed by the Atrial Fibrillation Investigators (AFI) and c of 0.74 (95% CI, 0.71-0.76) for the Stroke Prevention in Atrial Fibrillation (SPAF) III scheme. However, with a c statistic of 0.82 (95% CI, 0.80-0.84), the CHADS2 index was the most accurate predictor of stroke. The stroke rate per 100 patient-years without antithrombotic therapy increased by a factor of 1.5 (95% CI, 1.3-1.7) for each 1-point increase in the CHADS2 score: 1.9 (95% CI, 1.2-3.0) for a score of 0; 2.8 (95% CI, 2.0-3.8) for 1; 4.0 (95% CI, 3.1-5.1) for 2; 5.9 (95% CI, 4.6-7.3) for 3; 8.5 (95% CI, 6.3-11.1) for 4; 12.5 (95% CI, 8.2-17.5) for 5; and 18.2 (95% CI, 10.5-27.4) for 6.ConclusionThe 2 existing classification schemes and especially a new stroke risk index, CHADS2, can quantify risk of stroke for patients who have AF and may aid in selection of antithrombotic therapy.

Background— The rate of stroke in atrial fibrillation (AF) depends on the presence of comorbid conditions and the use of antithrombotic therapy. Although adjusted-dose warfarin is superior to aspirin for reducing stroke in AF, the absolute risk reduction of warfarin depends on the stroke rate with aspirin. This prospective cohort study tested the predictive accuracy of 5 stroke risk stratification schemes. Methods and Results— The study pooled individual data from 2580 participants with nonvalvular AF who were prescribed aspirin in a multicenter trial (Atrial Fibrillation, Aspirin, Anticoagulation I study [AFASAK-1], AFASAK-2, European Atrial Fibrillation Trial, Primary Prevention of Arterial Thromboembolism in patients with nonrheumatic Atrial Fibrillation in primary care study, and Stroke Prevention and Atrial Fibrillation [SPAF]-III high risk or SPAF-III low risk). There were 207 ischemic strokes during 4887 patient-years of aspirin therapy. All schemes predicted stroke better than chance, but the number of patients categorized as low and high risk varied substantially. AF patients with prior cerebral ischemia were classified as high risk by all 5 schemes and had 10.8 strokes per 100 patient-years. The CHADS ₂ scheme (an acronym for Congestive heart failure, Hypertension, Age >75, Diabetes mellitus, and prior Stroke or transient ischemic attack) successfully identified primary prevention patients who were at high risk of stroke (5.3 strokes per 100 patient-years). In contrast, patients identified as high risk by other schemes had 3.0 to 4.2 strokes per 100 patient-years. Low-risk patients identified by all schemes had 0.5 to 1.4 strokes per 100 patient-years of therapy. Conclusions— Patients with AF who have high and low rates of stroke when given aspirin can be reliably identified, allowing selection of antithrombotic prophylaxis to be individualized.

Knowledge of pharmacogenetics may help clinicians predict their patients’ therapeutic dose of warfarin, thereby decreasing the risk of bleeding during warfarin initiation. Our goal was to use pharmacogenetics to develop an algorithm that uses genetic, clinical, and demographic factors to estimate the warfarin dose a priori. We collected a blood sample, demographic variables, laboratory values, smoking status, names of medications, and dietary history from 369 patients who were taking a maintenance dose of warfarin. Using polymerase chain reaction, we genotyped each participant for the presence of 8 polymorphisms in the cytochrome P450 2C9 system. Using multiple regression, we quantified the association between warfarin dose and all factors. Advanced age, lower body surface area (BSA), and the presence of cytochrome P450 2C9 *2 or *3 single nucleotide polymorphisms were strongly associated (P < 0.001) with lower warfarin dose: the maintenance dose decreased by 8% per decade of age, by 13% per standard deviation decrease in BSA, by 19% per 2C9*2 allele, and by 30% per 2C9*3 allele. Warfarin doses were 29% lower in patients who took amiodarone, 12% lower in patients who took simvastatin, 21% lower in patients whose target INR was 2.5 rather than 3.0, and 11% lower in white rather than African-American participants (P < 0.05 for these comparisons). An algorithm that included these factors and one of borderline significance (sex), explained 39% of the variance in the maintenance warfarin dose. Use of this pharmacogenetic model had potential to prevent patients from being overdosed when initiating warfarin: we estimate that only 24 (6.5%) patients would have been overdosed by >2 mg/day with pharmacogenetic dosing compared to 59 (16%) patients who would have been overdosed if they had been prescribed the empirical dose of 5 mg/day (P < 0.001). In conclusion, the maintenance warfarin dose can be estimated from demographic, clinical, and pharmacogenetic factors that can be obtained at the time of warfarin initiation.

Background—: Recent studies have investigated alternatives to warfarin for stroke prophylaxis in patients with atrial fibrillation (AF), but whether these alternatives are cost-effective is unknown. Methods and Results—: On the basis of the results from Randomized Evaluation of Long Term Anticoagulation Therapy (RE-LY) and other trials, we developed a decision-analysis model to compare the cost and quality-adjusted survival of various antithrombotic therapies. We ran our Markov model in a hypothetical cohort of 70-year-old patients with AF using a cost-effectiveness threshold of $50 000/quality-adjusted life-year. We estimated the cost of dabigatran as US $9 a day. For a patient with an average risk of major hemorrhage (≈3%/y), the most cost-effective therapy depended on stroke risk. For patients with the lowest stroke rate (CHADS ₂ stroke score of 0), only aspirin was cost-effective. For patients with a moderate stroke rate (CHADS ₂ score of 1 or 2), warfarin was cost-effective unless the risk of hemorrhage was high or quality of international normalized ratio control was poor (time in the therapeutic range 72.6%). Neither dabigatran 110 mg nor dual therapy (aspirin and clopidogrel) was cost-effective. Conclusions—: Dabigatran 150 mg (twice daily) was cost-effective in AF populations at high risk of hemorrhage or high risk of stroke unless international normalized ratio control with warfarin was excellent. Warfarin was cost-effective in moderate-risk AF populations unless international normalized ratio control was poor.