Key result
The Acute Stroke AF Score predicts atrial fibrillation with an AUC of 0.79.
Why the study?
Atrial fibrillation is a common arrhythmia that increases stroke risk, and a predictive score for AF in acute ischemic stroke or TIA patients was needed.
Can a simple scoring system using age, NIHSS, and left atrial enlargement predict atrial fibrillation in patients with acute ischemic stroke or TIA?
Cohort (n=257)
No
Can a simple scoring system using age, NIHSS, and left atrial enlargement predict atrial fibrillation in patients with acute ischemic stroke or TIA?
Effect estimate: AUC 0.79
A simple clinical score using age, NIHSS, and left atrial enlargement can help identify patients at high risk for atrial fibrillation after an acute ischemic stroke or TIA.
ASAS may aid post-stroke AF risk stratification; hypothesis-generating pending prospective validation and outcome trials.
OBJECTIVE: Atrial fibrillation is a common arrhythmia that increases the risk of stroke by four- to five-fold. We aimed to establish a profile of patients with atrial fibrillation from a population of patients admitted with acute ischemic stroke or transient ischemic attack using clinical and echocardiographic findings. METHODS: We evaluated patients consecutively admitted to a tertiary hospital with acute ischemic stroke or transient ischemic attack. Subjects were divided into an original set (admissions from May 2009 to October 2010) and a validation set (admissions from November 2010 to April 2013). The study was designed as a cohort, with clinical and echocardiographic findings compared between patients with and without atrial fibrillation. A multivariable model was built, and independent predictive factors were used to produce a predictive grading score for atrial fibrillation (Acute Stroke AF Score-ASAS). RESULTS: A total of 257 patients were evaluated from May 2009 to October 2010 and included in the original set. Atrial fibrillation was diagnosed in 17.5% of these patients. Significant predictors of atrial fibrillation in the multivariate analysis included age, National Institutes of Health Stroke Scores, and the presence of left atrial enlargement. These predictors were used in the final logistic model. For this model, the area under the receiver operating characteristic curve was 0.79. The score derived from the logistic regression analysis was The model developed from the original data set was then applied to the validation data set, showing the preserved discriminatory ability of the model (c statistic = 0.76). CONCLUSIONS: Our risk score suggests that the individual risk for atrial fibrillation in patients with acute ischemic stroke can be assessed using simple data, including age, National Institutes of Health Stroke Scores at admission, and the presence of left atrial enlargement.
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Figueiredo et al. (2014) conducted a cohort in Acute ischemic stroke or transient ischemic attack (n=257). Acute Stroke AF Score-ASAS was evaluated on Atrial fibrillation (AUC 0.79). The Acute Stroke AF Score-ASAS, incorporating age, NIHSS, and left atrial enlargement, predicted atrial fibrillation with an AUC of 0.79 in the derivation cohort and 0.76 in validation.
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