INTRODUCTION: The aims of this study are to describe the incidence of paroxysmal atrial fibrillation (pAF) in patients with ischemic stroke (IS) or transient ischemic attack (TIA), and to create a risk prediction model, using immediately available clinical data associated with new pAF diagnosis. METHODS: We analyzed data from the BASICMAR stroke register, with 5 inclusion criteria: (1) diagnosis of IS/TIA; (2) no history of AF or structural cardiopathy; (3) stroke unit (SU) monitoring after normal electrocardiogram in the emergency room; (4) complete etiologic study; and (5) 3-month follow-up. We investigated clinical predictors of pAF detection; we analyzed newly diagnosed pAF according to 4 cardiac monitoring screening methods and created a pAF-risk prediction model. RESULTS: The final cohort included 1,240 patients. pAF was diagnosed in 139 patients (11.2%), the majority at the SU (54.7%). Multivariate predictors of new-pAF diagnosis during 3-month follow-up after ischemic event were age 75 years, female gender, history of congestive heart failure, and initial National Institute of Health Stroke Scale 15, with a predicted AF risk of 64%. CONCLUSIONS: This risk prediction model can be helpful to estimate the risk of an underlying pAF within 3 months after suffering an IS/TIA, contributing to increased AF detection efforts, thereby starting the correct secondary prevention treatment.
INTRODUCTION: The aims of this study are to describe the incidence of paroxysmal atrial fibrillation (pAF) in patients with ischemic stroke (IS) or transient ischemic attack (TIA), and to create a risk prediction model, using immediately available clinical data associated with new pAF diagnosis. METHODS: We analyzed data from the BASICMAR stroke register, with 5 inclusion criteria: (1) diagnosis of IS/TIA; (2) no history of AF or structural cardiopathy; (3) stroke unit (SU) monitoring after normal electrocardiogram in the emergency room; (4) complete etiologic study; and (5) 3-month follow-up. We investigated clinical predictors of pAF detection; we analyzed newly diagnosed pAF according to 4 cardiac monitoring screening methods and created a pAF-risk prediction model. RESULTS: The final cohort included 1,240 patients. pAF was diagnosed in 139 patients (11.2%), the majority at the SU (54.7%). Multivariate predictors of new-pAF diagnosis during 3-month follow-up after ischemic event were age 75 years, female gender, history of congestive heart failure, and initial National Institute of Health Stroke Scale 15, with a predicted AF risk of 64%. CONCLUSIONS: This risk prediction model can be helpful to estimate the risk of an underlying pAF within 3 months after suffering an IS/TIA, contributing to increased AF detection efforts, thereby starting the correct secondary prevention treatment.