BACKGROUND AND PURPOSE: Detecting paroxysmal atrial fibrillation (pAF) soon after acute cerebral ischaemia has a major impact on secondary stroke prevention. Recently, the STAF score, a composite of clinical and instrumental findings, was introduced to identify stroke patients at risk of pAF. We aimed to validate this score in an independent study population. METHODS: Consecutive patients admitted to our stroke unit with acute ischaemic stroke were prospectively enrolled. The diagnostic work-up included neuroimaging, neuroultrasound, baseline 12-channel electrocardiogram (ECG), 24-h Holter ECG, continuous ECG monitoring, and echocardiography. Presence of AF was documented according to the medical history of each patient and after review of 12-lead ECG, 24-h Holter ECG, or continuous ECG monitoring performed during the stay on the ward. Additionally, a telephone follow-up visit was conducted for each patient after 3 months to inquire about newly diagnosed AF. Items for each patient-age, baseline NIHSS, left atrial dilatation, and stroke etiology according to the TOAST criteria - were assessed to calculate the STAF score. RESULTS: Overall, 584 patients were enrolled in our analysis. AF was documented in 183 (31.3%) patients. In multivariable analysis, age, NIHSS, left atrial dilatation, and absence of vascular etiology were independent predictors for AF. The logistic AF-prediction model of the STAF score revealed fair classification accuracy in receiver operating characteristic curve analysis with an area under the curve of 0.84. STAF scores of ≥5 had a sensitivity of 79% and a specificity of 74% for predicting AF. CONCLUSION: The value of the STAF score for predicting the risk of pAF in stroke patients is limited.
BACKGROUND AND PURPOSE: Detecting paroxysmal atrial fibrillation (pAF) soon after acute cerebral ischaemia has a major impact on secondary stroke prevention. Recently, the STAF score, a composite of clinical and instrumental findings, was introduced to identify strokepatients at risk of pAF. We aimed to validate this score in an independent study population. METHODS: Consecutive patients admitted to our stroke unit with acute ischaemic stroke were prospectively enrolled. The diagnostic work-up included neuroimaging, neuroultrasound, baseline 12-channel electrocardiogram (ECG), 24-h Holter ECG, continuous ECG monitoring, and echocardiography. Presence of AF was documented according to the medical history of each patient and after review of 12-lead ECG, 24-h Holter ECG, or continuous ECG monitoring performed during the stay on the ward. Additionally, a telephone follow-up visit was conducted for each patient after 3 months to inquire about newly diagnosed AF. Items for each patient-age, baseline NIHSS, left atrial dilatation, and stroke etiology according to the TOAST criteria - were assessed to calculate the STAF score. RESULTS: Overall, 584 patients were enrolled in our analysis. AF was documented in 183 (31.3%) patients. In multivariable analysis, age, NIHSS, left atrial dilatation, and absence of vascular etiology were independent predictors for AF. The logistic AF-prediction model of the STAF score revealed fair classification accuracy in receiver operating characteristic curve analysis with an area under the curve of 0.84. STAF scores of ≥5 had a sensitivity of 79% and a specificity of 74% for predicting AF. CONCLUSION: The value of the STAF score for predicting the risk of pAF in strokepatients is limited.
Authors: Vincent N Thijs; Johannes Brachmann; Carlos A Morillo; Rod S Passman; Tommaso Sanna; Richard A Bernstein; Hans-Christoph Diener; Vincenzo Di Lazzaro; Marilyn M Rymer; Laurence Hogge; Tyson B Rogers; Paul D Ziegler; Manish D Assar Journal: Neurology Date: 2015-12-18 Impact factor: 9.910