Abstract Number: Esoc2026lb151 Af Screening to Prevent Ischaemic Stroke and Health Economic Impacts (The Aspire Study)

Abstract Background and aims Atrial fibrillation (AF) causes ischaemic stroke but population AF screening is not recommended. We developed and externally validated a model to guide AF screening and assessed health economic impact. Methods We analysed clinical demographics, NT-proBNP concentrations and artificial intelligence analysis of ECG data from people with no prior AF in the Generation Scotland study, with external validation in UK Biobank. Record linkage identified people with AF during follow-up. A clinical model for incident AF was developed using penalised logistic regression with Lasso modelling (80:20 training/testing). We assessed incorporating NT-proBNP or ECG data by De Long’s test. A decision-analytic model assessed cost-effectiveness of screening everyone or using the clinical model to guide AF screening, compared with no screening. Results We analysed 23,830 people: 14,061 (59%) female and mean (SD) age 47.0 (15.3) years. AF was diagnosed in 901 people (3.8%). The clinical model included age (OR 1.20, 1.13-1.28), age2 (OR 0.99, 0.99-1.00), weight (OR 1.03, 1.02-1.03), ischaemic heart disease (OR 1.63, 1.31-2.02) and heart failure (OR 3.78, 2.03-7.03). AUROC was 84.1% (82.1-86.1%) in test data and 75.4% (75.1-75.6%) in external validation. Model performance improved with logeNT-proBNP (86.5%, 84.5-88.5%; p0.001) but not ECG data (84.5%, 82.2-86.5%; p=0.76). The quality-adjusted life years (QALYs) gained and cost reduction per-person was 0.05 years and £656 for screening everyone; and 0.04 and £548 for the clinical model to guide screening. Conclusions A clinical model could guide AF screening to prevent stroke and can be augmented by NT-proBNP. Screening everyone and using a clinical model is cost-effective. Conflict of interest