Supplementary Material for: Predicting Incident Atrial Fibrillation After Stroke: A Scoping Review of Clinical Scores, Biomarkers, and AI-enhanced Strategies

Post-stroke atrial fibrillation (AFib) is a frequent yet undetected complication, particularly in resource-limited settings, where systematic screening remains challenging. Timely identification is essential for guiding anticoagulation strategies and reducing recurrent stroke risk. This scoping review synthesizes evidence on predictive strategies integrating artificial intelligence, circulating biomarkers, and advanced rhythm-monitoring modalities in adults with ischemic stroke or transient ischemic attack without known AFib. Predictive variables from conventional clinical scores and modern AI-based models were harmonized into a unified framework, highlighting incremental contributions from natriuretic peptides, imaging radiomics, and electronic health record–derived laboratory parameters. A novel analytical construct—area under the curve (AUC)–cost–feasibility mapping—was introduced to compare diagnostic strategies, including risk scores, handheld and patch electrocardiography, smartwatch-based photoplethysmography (with ECG confirmation required for diagnosis), and implantable loop recorders, with explicit consideration of scalability in low- and middle-income countries. Based on this synthesis, a tiered diagnostic pathway is proposed, combining clinical risk stratification with biomarker-guided triage (particularly NT-proBNP and MR-proANP) to inform allocation of extended monitoring resources, thereby optimizing diagnostic yield and cost-effectiveness. Persistent knowledge gaps include the absence of standardized biomarker thresholds, limited head-to-head evaluations of AI-enabled workflow in post-stroke populations, insufficient external validation in diverse populations, and a lack of prospective cost-effectiveness analyses. By integrating predictive domains, quantifying performance–cost trade-offs, and outlining an implementation-oriented, risk-stratified strategy, this review aims to inform AFib screening after stroke from theoretical innovation toward context-adapted clinical application, offering a structured framework to guide both research and practice in diverse healthcare environments.