Selecting Patients With Atrial Fibrillation for Anticoagulation
Stroke Risk Stratification in Patients Taking Aspirin
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 absoluterisk reduction of warfarin depends on the stroke rate with aspirin. This prospective cohort study tested the predictiveaccuracy of 5 stroke risk stratification schemes.
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. 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.
T he rate of stroke in nonvalvular atrial fibrillation (AF) ranges widely and depends on the presence of prior cerebral ischemia, comorbid conditions, and use of antithrombotic therapy. Without antithrombotic therapy, the rate varies from fewer than 2 to more than 10 strokes per 100 patient-years. 1–7 Although adjusted-dose warfarin is superior to aspirin for reducing stroke in AF patients, the absolute risk reduction is determined by the stroke risk with aspirin therapy. Thus, quantifying the risk of stroke is crucial for determining which AF patients would benefit most from warfarin therapy. Patients whose risk is less than 2 strokes per 100 patient-years with aspirin have little to gain from warfarin therapy; for these patients, the risks of warfarin tend to outweigh any benefits. A risk stratification scheme that reliably identified these low-risk patients could spare them the risks, inconvenience, and costs associated with anticoagulation. In contrast, for AF patients whose risk exceeds 4 strokes per 100 patient-years of aspirin therapy, warfarin therapy consistently improves quality-adjusted survival. Between these 2 extremes are patients for whom the key issue
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is whether stroke risk can be quantified reliably so that antithrombotic therapy can be judiciously selected on the basis of stroke risk, hemorrhage risk, and individual preferences.
Risk stratification schemes that accurately and reliably stratify stroke risk could influence the antithrombotic management of millions of people who have AF. Because patients with a prior stroke or transient ischemic attack (TIA) are at high risk of stroke, the greatest need is to quantify stroke risk
in the AF primary prevention population. Here, we use prospective data to test the predictive accuracy of 5 widely available stroke risk stratification schemes and provide reliable guidance to clinicians selecting antithrombotic therapy.
Risk Stratification Schemes
Multivariate analyses of prospective cohorts of AF patients who were prescribed aspirin or no antithrombotic therapy yielded independent predictors of stroke that formed the basis of 5 previously
published risk stratification schemes. In 1994, the Atrial Fibrillation Investigators (AFI) conducted a multivariate analysis of pooled data from 1593 untreated AF participants in 5 randomized clinical trials. Participants with prior cerebral ischemia (either stroke or TIA), hypertension, or diabetes mellitus were at high risk of stroke; patients without these risk factors were at moderate risk of stroke if older than 65 years and at low risk otherwise. The Stroke Prevention and Atrial Fibrillation (SPAF) investigators developed a classification scheme from 854 SPAF I and II participants treated with aspirin. Four factors independently predicted a high risk of stroke: prior cerebral ischemia, the combination of age greater than 75 years plus female gender, left ventricular dysfunction (defined as recent clinical heart failure or left ventricular fractional shortening ≤25% by echocardiography), and systolic blood pressure 160 mm Hg. SPAF participants with a history of hypertension but blood pressure ≤ 160 mm Hg were found to have a moderate risk (--3 strokes per 100 patient-years), and participants with none of these factors were at low risk of stroke. In 1998 and 2001, the American College of Chest Physicians (ACCP) Consensus Conference on Antithrombotic Therapy classified patients as high risk if they had prior cerebral ischemia (or systemic embolism), hypertension, congestive heart failure (either clinical heart failure or poor systolic function on echocardiography), age ≥75 years, or at least 2 moderate-risk factors. The moderate-risk factors were age 65 to 75 years, diabetes mellitus, and coronary artery disease. Patients with 1 moderate-risk factor were classified as moderate risk, and patients with none of the risk factors were classified as low risk. In 2001, an amalgamation of the AFI and SPAF schemes led to the CHADS 2 scheme. 2 The CHADS 2 acronym was derived from the individual stroke risk factors: Congestive heart failure, Hypertension, Age 75 years, Diabetes mellitus, and prior Stroke or TIA. Two points were given for prior stroke or TIA (hence, the subscripted «2»), and 1 point was assigned for each of the other factors. The point system was designed to simplify the determination of stroke risk in general practice. CHADS 2 stroke rates were calculated in 1733 Medicare beneficiaries in the National Registry of Atrial Fibrillation using International Classification of Diseases codes 434 (occlusion of cerebral arteries), 435 (transient cerebral ischemia), and 436 (acute, but ill-defined, cerebrovascular disease). The expected stroke rate (95% CI) per 100 patient-years without antithrombotic therapy increases by a factor of 1.5 for each 1-point increase in the CHADS 2 score: 1.9 (1.2 to 3.0) for a score of 0; 2.8 (2.0 to 3.8) for 1; 4.0 (3.1 to 5.1) for 2; 5.9 (4.6 to 7.3) for 3; 8.5 (6.3 to 11.1) for 4; 12.5 (8.2 to 17.5) for 5; and 18.2 (10.5 to 27.4) for 6. In 2003, Wang et al 18 developed a risk classification scheme based on 868 Framingham participants, some of whom were taking warfarin or aspirin therapy. Using the coefficients from a Cox proportional survival model, they developed a point system based on age (0 to 10 points), gender (6 points for female; 0 for male), blood pressure (0 to 4 points), diabetes mellitus (4 points), and prior stroke or TIA (6 points) to develop a scheme to predict the combination of ischemic plus hemorrhagic stroke. Whether the Framingham scheme will predict ischemic stroke in other AF populations is not clear.
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For a variety of reasons, we evaluated only these 5 risk stratification schemes and excluded others. We excluded schemes that were based entirely on retrospective data. We excluded 2 schemes
that were based on data used in the present analysis and another because the other study focused exclusively on secondary prevention. We excluded the initial SPAF I scheme 6 because it was
superseded by the subsequent SPAF and AFI schemes, both of which used SPAF I data. We excluded schemes that required the use of echocardiography to risk-stratify patients 23–27 because we did not
have echocardiographic results on all participants and because we wished to validate a scheme that could predict stroke on the basis of clinical risk factors.
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