Demographic Refinement and Atrial Fibrillation Type in Stroke Risk Stratification Beyond CHA2DS2 VASc

Introduction: The CHA2DS2 VASc score is widely used for stroke risk stratification in atrial fibrillation (AF). Efforts to improve prediction using demographic refinements have uncertain incremental value, particularly in multi-ethnic populations. We evaluated whether demographic modification or AF type provides additional discriminatory value. Methods: We conducted a retrospective nested case-control study of patients with AF diagnosed prior to the fifth Auckland Regional Community Stroke Study (September 2020-August 2021). Cases with ischaemic stroke or transient ischaemic attack were identified from this population-based registry with central adjudication. Controls were randomly selected from the National Minimum Dataset, stratified by ethnicity. Predictors included CHA2DS2 VASc components, demographic refinements (alternative age transformations, ethnicity, exclusion of sex), and AF type. The primary baseline model was a multivariable logistic regression model using standard CHA2DS2 VASc predictors as covariates. The traditional point-based CHA2DS2 VASc score was evaluated separately for comparison. Discrimination was assessed using area under the receiver operating characteristic curve (AUC). Results: The study included 1,908 patients (300 cases). A logistic regression model using standard CHA2DS2 VASc predictors demonstrated moderate discrimination (AUC 0.68 [95% CI 0.65-0.71]). The traditional point-based CHA2DS2 VASc score showed lower discrimination (AUC 0.63 [95% CI 0.60-0.66]; ΔAUC +0.05; p=0.0003). Demographic refinements did not improve discrimination (ΔAUC ≤0.01). Addition of AF type modestly increased discrimination (AUC 0.71; ΔAUC +0.03; p=0.015), with greater improvement in non-anticoagulated patients (ΔAUC +0.05). Conclusion: Demographic refinements, including ethnicity, provide limited incremental value beyond CHA2DS2 VASc, whereas AF type offers a modest discriminatory signal. This finding is hypothesis-generating and requires external validation before clinical implementation is considered.