A Score for Predicting Paroxysmal Atrial Fibrillation in Acute Stroke Patients: iPAB Score

Background Detection of paroxysmal atrial fibrillation (PAF) after a stroke is challenging. The purpose of this study was to develop a clinical score to predict PAF in a cohort of acute ischemic stroke patients prospectively and to validate it in an independent cohort. Methods Consecutive acute ischemic stroke patients without permanent atrial fibrillation were enrolled in a derivation sample (n = 294) or a validation sample (n = 155). We developed a score for predicting PAF by independent risk factors derived from a logistic regression analysis of the derivation cohort and validated the score in the external cohort. Results Multivariate analysis in the derivation cohort identified 3 variables independently associated with PAF. We calculated a score from these variables (history of arrhythmia or antiarrhythmic agent use [yes, 3 points], left atrial dilation [≥40 mm, 1 point], brain natriuretic peptide [BNP, ≥50 pg/mL, 1 point; ≥90 pg/mL, 2 points; ≥150 pg/ml, 3 points], total score, 0-7). The iPAB score (identified by past history of arrhythmia or antiarrhythmic agent use, atrial dilation, and BNP elevation) predicted PAF in the derivation ( c statistic, .90) and validation (.94) cohorts at levels statistically superior to other biomarkers and clinical scores. For a total score 2 or more, the sensitivity and specificity were 93% and 71%, respectively. For a total score of 4 or more, the corresponding values were 60% and 95%. Conclusions Our prospective study suggests that this simple risk score superior to other scores help clinicians predict PAF or identify good candidates for further evaluation to detect PAF.