Atrial fibrillation detection after embolic stroke of undetermined source: Development and validation of the CATCH-AF score

Background: Embolic stroke of undetermined source (ESUS) accounts for up to one quarter of ischemic strokes, with occult atrial fibrillation (AF) as a key underlying cause. Implantable cardiac monitors (ICMs) markedly improve AF detection but are limited by cost and resource demands. Existing AF-prediction models show modest accuracy and lack longitudinal validation. We developed and validated the CATCH-AF score to provide a simple, clinically applicable tool for stratifying early and long-term AF risk after ESUS. Methods: We analyzed 543 consecutive ESUS patients systematically monitored with ICMs. Variable selection used LASSO-penalized Cox regression. Model performance was assessed with time-dependent ROC curves, restricted mean survival time (RMST) analysis, and 10-fold cross-validation. To evaluate geographic generalizability, internal–external cross-validation was performed across seven participating centers, estimating discrimination and calibration for each held-out cohort. Based on the final multivariable model, a point-based score was derived including age, coronary artery disease, heart failure, and prior transient ischemic attack or ischemic stroke. Results: During 1558.5 patient-years of follow-up, 118 patients (22%) developed new AF. The CATCH-AF score showed excellent discrimination (AUC 0.85, 95% CI 0.82–0.89), stable over 4.5 years (0.84–0.87). Compared with low-risk patients (0–2 points), those at high risk (⩾5 points) had a 19-fold higher hazard of AF detection (HR 19.2, 95% CI 9.4–39.4; p < 0.001) and 918 fewer AF-free days (95% CI −1080 to −757). Conclusions: The CATCH-AF score provides a robust, interpretable, and easily applicable tool for predicting AF after ESUS, supporting targeted and cost-effective rhythm monitoring.