Stratifying Stroke Risk in Atrial Fibrillation: Beyond Clinical Risk Scores

Shadi Yaghi, MD; Hooman Kamel, MD

Disclosures

Stroke. 2017;48(10):2665-2670. 

In This Article

Prediction of Stroke Risk Based on Clinical Factors

Risk Factors

Several studies have reported risk factors for stroke in patients with AF. A pooled analysis of 5 trials with 5956 patient-years of follow-up found that independent risk factors for ischemic stroke were age (relative risk [RR] per 10 years, 1.4), prior stroke or transient ischemic attack (TIA; RR, 2.5), hypertension (RR, 1.8), diabetes mellitus (RR, 1.7), and congestive heart failure (RR, 1.4).[6] In patients <65 years of age who had none of these risk factors, the annual rate of stroke was 1.0% (95% confidence interval [CI], 0.3%–3.1%) with antiplatelet or no antithrombotic therapy, whereas in patients >75 years of age with one or more of these risk factors, the annual stroke rate was 8.1% (95% CI, 4.7%–13.9%).[6] Another systematic review, including 7 studies with >12 000 patients, identified the following factors to be associated with stroke or systemic embolism: prior stroke or TIA (RR, 2.5; 95% CI, 1.8–3.5), increasing age (RR per decade, 1.5; 95% CI, 1.3–1.7), hypertension (RR, 2.0; 95% CI, 1.6–2.5), and diabetes mellitus (RR, 1.7; 95% CI, 1.4–2.0).[7]

A less well-established risk factor for stroke in AF is female sex. A study from a Swedish hospital discharge registry, featuring 100 802 patients with a median follow-up of 1.2 years, found an association between female sex and the risk of stroke (hazard ratio [HR], 1.18; 95% CI, 1.12–1.24).[8] Women with AF and no other stroke risk factors (often termed lone AF) had a nonsignificantly higher stroke risk when compared with men (overall rate, 0.7% versus 0.5%; P=0.09).[8] The association between female sex and stroke risk in AF has been also reported elsewhere.[9,10] On the contrary, some studies have found no association between female sex and stroke in AF.[7]

After publication of the pooled analyses of early trials in AF discussed above, several other risk factors of stroke in AF were reported. Several studies have shown an association of coronary artery disease,[11,12] peripheral vascular disease,[13] and complex aortic plaque[14] with the risk of stroke or systemic embolism in patients with AF. In addition, renal disease has recently emerged as a possible risk factor for stroke in AF. In a study with 33 165 person-years of follow-up, the risk of thromboembolism in AF was increased in the presence of proteinuria (RR, 1.54; 95% CI, 1.29–1.85) or an estimated glomerular filtration rate <45 mL/min per 1.73 m[2] (compared with ≥60) even after adjustment for other risk factors (RR, 1.39; 95% CI, 1.13–1.71).[15] On the contrary, another study with 5912 patients and 1 year of follow-up found no association between renal impairment and stroke risk in AF after adjustment for known risk factors (HR, 1.06; 95% CI, 0.75–1.49).[16]

Risk Scores

Clinical scores have been developed to help predict the risk of stroke and systemic embolism in patients with AF, with the ultimate goal of determining whether that risk is high enough to warrant the bleeding risks associated with anticoagulant therapy. The CHADS2 score assigns 1 point each for congestive heart failure, hypertension, age >=75 years, and diabetes mellitus, and 2 points for prior stroke or TIA. The CHADS2 score was one of the first published stroke risk prediction tools for management of AF. In the CHADS2 derivation cohort, with 2121 patient-years of follow-up, each 1-point increase in the CHADS2 score was associated with a 1.5-fold higher hazard of stroke, and the score had good predictive ability with a C statistic of 0.82.[17] External validation studies showed fair-to-good predictive ability of the CHADS2 score, with C statistics ranging between 0.56 and 0.82.[18] Despite these validation studies, major limitations of the CHADS2 score have become apparent because its use has become more widespread. First, the CHADS2 score has also been shown to predict hemorrhagic complications in patients with AF.[19] This means that patients with a high predicted risk of thromboembolic events are also the same patients with a high predicted risk of hemorrhagic complications, which complicates decisions about anticoagulant therapy. More importantly, the score suffers from significant heterogeneity in actual stroke risk in patients labeled as low risk based on their CHADS2 score. In the overall group of patients assigned a CHADS2 score of 0, the annual stroke risk can ranges between 0 and 3%.[20] This is problematic if the score is used to withhold anticoagulant therapy in those with low scores—a purpose for which it is often used.

To better risk stratify patients considered to be low risk based on the CHADS2 score, investigators designed the CHA2DS2-VASc score. This score builds on the CHADS2 score by adding an extra point each for female sex and vascular disease (which includes both coronary heart disease and peripheral vascular disease), and dividing age into 3 categories (<60 years, 60–74 years, and >=75 years) instead of the 2 categories in the original CHADS2 score.[21] It seems that the CHA2DS2-VASc score outperforms the CHADS2 score in discriminating stroke risk in the group of patients with a CHADS2 score of 0 or 1.[21,22] The CHA2DS2-VASc score is especially helpful in that patients classified as low risk truly do seem to be at low risk of stroke and may safely be managed without anticoagulant therapy.[18] In addition to the CHADS2 and CHA2DS2-VASc scores, several other clinical scores have been proposed.[23–26]

A shortcoming shared by all of these clinical risk prediction scores is that they include general risk factors for stroke that apply to patients with and without AF. It is intuitive that stroke risk increases with the general burden of vascular disease. In fact, studies have shown that the CHADS2 and CHA2DS2-VASc scores predict stroke risk even in patients without AF.[27] On the contrary, specific biomarkers reflecting dysfunction of the left atrium or left atrial appendage (LAA) may be more predictive of the type of stroke that is most likely amenable to prevention with anticoagulant therapy.

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