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Tze-Fan Chao

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Open access Aug 2026

Phenotypic clustering and ABC pathway adherence in patients with atrial fibrillation at high risk of bleeding and stroke: Insights from three global registries.

BACKGROUND Patients with atrial fibrillation (AF) who are at increased risk of both thrombotic and haemorrhagic events represent a heterogeneous and broad clinical entity, characterized by the presence of several Janus-faced risk factors. We aimed to identify clinical phenotypes and assess the association of ABC pathway adherence with one-year outcomes in patients with AF at high risk of both stroke and bleeding. METHODS AF patients who had HAS-BLED score ≥3 and CHA2DS2-VASc score ≥2 were included. Hierarchical clustering was applied to identify phenotypic subgroups. We assessed the impact on net adverse clinical event (NACE) of adherence to the integrated care based on the Atrial fibrillation Better Care (ABC) pathway. RESULTS A total of 2,535 patients (mean age 75.4 ± 7.8 years; 58.3% male) were enrolled. Cluster I had the highest rates of prior thromboembolic and haemorrhagic events with the lowest comorbidity burden; Cluster II comprised the oldest patients with the highest prevalence of dyslipidaemia, heart failure, and peripheral artery disease; Cluster III was the youngest with the highest BMI and alcohol use. Cluster II (aOR 1.93, 95% CI 1.37-2.78), and Cluster III (aOR 1.65, 95% CI 1.10-2.50) were associated with a higher risk of all-cause death compared to Cluster I. Among patients with available ABC pathway data, adherence was associated with lower odds of 1-year MACE (OR 0.39, 95% CI 0.15-0.82). CONCLUSION Three distinct phenotypic clusters were identified, each with heterogeneous clinical characteristics and outcomes, underscoring the need for more individualised, phenotype-informed management strategies in this complex patient population.

A. Askarinejad, T. Bucci, Enrico Tartaglia et al. · 0 citations
Open access Aug 2026

Development and External Validation of the GLORIA-AF Bleeding Weighted Risk Score for Patients with Atrial Fibrillation.

AIMS Major bleeding remains a major barrier to optimal anticoagulation in patients with atrial fibrillation (AF). We aimed to develop and externally validate a weighted score that balances simplicity and prediction for 1-year major bleeding prediction. METHODS Using prospective multinational GLORIA-AF Phase II/III data, we developed the GLORIA-AF Bleeding Weighted Risk Score using LASSO-penalized regression with stability selection, coefficient-rescaling and internal validation. The score was externally evaluated in EORP-AF and APHRS-AF registries. Discrimination, calibration and clinical benefit were assessed using C-index, observed-to-expected ratio, calibration plot and decision-curve analysis, and compared with HAS-BLED, unweighted GLORIA-AF score and full multivariable Cox model. RESULTS Among 20,250 eligible derivation cohort patients (69.9 [10.3] years; 9,092 female [44.9%]), 317 (1.6%) had major bleeding during 1-year follow-up. The derived score ranges from 0 to 22, with the highest weight (5) assigned to age >65 years, followed by abnormal kidney function (3). The derived score achieved C-index of 0.688 (95% CI: 0.660-0.717), outperforming HAS-BLED (C-index: 0.631, 95% CI: 0.604-0.658; P < 0.001), while preserving discrimination comparable to full multivariable regression (C-index: 0.690; 95%CI: 0.661-0.719; P = 0.084). Calibration was good (O:E ratio: 0.996) and DCA showed greater net benefit than HAS-BLED across 1% to 3% thresholds. Among 9,752 external validation patients, 148 (1.5%) had major bleeding. The derived score achieved C-index of 0.674 (95% CI: 0.643-0.705; P < 0.001), with better discrimination, calibration and clinical benefit than HAS-BLED. CONCLUSIONS The GLORIA-AF Bleeding Score showed modestly higher discrimination than HAS-BLED for 1-year major bleeding prediction while retaining clinical interpretability and usability. External validation in independent European and Asia-Pacific registries further supports its transportability beyond the derivation population.

Yi-Fan Xie, Wenhui Li, Yanda Meng et al. · 0 citations

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