Abstract
INTRODUCTION: The aim of the present study was to predict paroxysmal atrial fibrillation (PAF) in acute ischemic stroke patients with presumed cryptogenic embolic etiology. METHODS: In this retrospective cohort study, demographics, blood tests, data of neuroimaging studies such as non-contrast computed tomography (NCCT), magnetic resonance imaging (MRI), standard 12-lead electrocardigraphy (ECG), 24-hour Holter ECG, echocardiography was collected. The diagnostic work-up to detect atrial fibrillation (AF) was either medical history of the patient or 12-lead ECG or 24-hour Holter ECG or continuous ECG monitoring. Score for the targeting of atrial fibrillation (STAF) was calculated for all patients. Cryptogenic ischemic stroke (CS) patients with and without documented AF were recorded. RESULTS: Between July 2014 and December 2015, a total of 133 of the 258 patients with CS were included in this study. Overall, 133 patients were enrolled and AF was detected in 30 (22.6%) patients. In univariate analysis gender (p<0.001), age (p=0.001), smoking habit (p=0.004), aortic and mitral valve insufficiency (p=0.014 and p=0.021), left ventricular systolic dysfunction (p=0.04), and left atrial dilatation (p=0.03) were predictors of AF but multivariate analysis showed that only gender and age were independent predictors of AF in patients with presumed cryptogenic ischemic stroke. According to ROC analysis, area under the curve was 70% and the sensitivity and specificity of STAF score of ≥5 was 86% and 71% respectively. CONCLUSION: STAF score predicted with fair accuracy, and has a limited use for the risk of PAF in stroke patients.