Predicting atrial fibrillation after cryptogenic stroke via a clinical risk score - a prospective observational study

BACKGROUND Atrial fibrillation (AF) often remains undiagnosed in cryptogenic stroke (CS), mostly because of limited availability of cardiac long-term rhythm monitoring. There is an unmet need for a pre-selection of CS patients benefiting from such work-up. We therefore developed a clinical risk score for the prediction of AF after CS and evaluated its performance over one year of follow-up. METHODS Our proposed risk score ranges from 0 to 16 points and comprises variables known to be associated with occult AF in CS patients including age, NT-proBNP, electro- and echocardiographic features (supraventricular premature beats, atrial runs, atrial enlargement, left ventricular ejection fraction) and brain imaging markers (multi-territory/prior cortical infarction). We prospectively followed all CS patients admitted to our Stroke Unit between March 2018 to August 2019 for AF detection over one year after discharge. RESULTS During the one-year follow-up, we diagnosed 24 (16%) out of 150 CS patients with AF (detected via ECG-controls, n=18; loop recorder-monitoring, n=6). Our predefined AF risk score (cutoff ≥4 points; highest Youden's Index) had a sensitivity of 92% and a specificity of 67% for one-year prediction of AF. Notably, only two CS patients with<4 score points were diagnosed with AF later on (negative predictive value: 98%). CONCLUSIONS We here present a clinical risk score for one-year prediction of AF in CS with high sensitivity, reasonable specificity, and excellent negative predictive value. Generalizability of our score needs to be tested in external cohorts with continuous cardiac rhythm monitoring.
as reported in: Eur J Neurol. 2021 Sep 14 [Epub ahead of print]