Abstract
Background and purpose: Detecting cardioembolic stroke soon after acute cerebral ischemia has a major impact on secondary stroke prevention. Recently, the Score for the Targeting of Atrial Fibrillation (STAF) was introduced to identify stroke patients at risk of atrial fibrillation. However, whether the STAF score could be a useful approach to differentiate cardioembolic stroke from other stroke subtypes is unclear. Methods: Consecutive patients with acute ischemic stroke that were admitted to our stroke center were enrolled. Each patient was assessed (age, baseline National Institutes of Health Stroke Scale, left atrial dilatation and absence of vascular etiology) to calculate the STAF score. A follow-up visit was conducted for each patient during hospitalization to determine the diagnosed stroke etiology according to the Trial of Org 10172 in Acute Stroke Treatment criteria. Results: The median and interquartile range of the STAF score was significantly higher in the cardioembolic than in the non-cardioembolic group [6 (2) vs. 2 (3), p < 0.001]. The discriminating ability of the STAF score model was good as demonstrated by the receiver operating characteristic curve. The area under the curve (AUC) of STAF score (AUC = 0.98; 95% CI, 0.96–0.99) was significantly greater than B-type natriuretic peptide (AUC = 0.87; 95% CI, 0.83–0.91) (p < 0.05). The optimal STAF cut-off value was ≥ 5, which diagnosed cardioembolic stroke with a sensitivity of 90% and specificity of 95%. Conclusions: The STAF score is a simple and accurate tool that can discriminate the cardioembolic stroke from other types during hospitalization for acute ischemic stroke.
KEYWORDS:
Acknowledgement
The funders had no role in the study design, data collection, data analysis, decision to publish or manuscript preparation.
Declaration of interest
This study was supported by the Key Medical Disciplines and Specialities Program of Guangzhou, the Scientific Research Project of the Guangzhou Education Bureau [grant number 1201421371] and the Science and Technology Plan Project of Guangdong Province [grant number 2015A030302091].
Declaration of interest
The authors declare no conflicts of interest.