Atrial Fibrillation and Stroke Risk: Emerging Biomarkers and Preventive Strategies—A Prospective Observational Study.
DOI:
https://doi.org/10.51168/1abfmg97Keywords:
Atrial fibrillation, Stroke, Biomarkers, N-terminal pro-B-type natriuretic peptide (NT-proBNP), D-dimer, High-sensitivity C-reactive protein (hs-CRP), PreventionAbstract
Background:
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is associated with a five-fold increased risk of ischemic stroke. Conventional risk stratification tools, such as the CHA₂DS₂-VASc score, may not fully identify patients at high thromboembolic risk. Emerging biomarkers may improve stroke prediction and guide preventive strategies.
Aim:
To evaluate the role of emerging biomarkers in predicting stroke risk among patients with atrial fibrillation and assess their utility alongside conventional clinical risk assessment.
Methods:
A hospital-based prospective observational study was conducted at Patna Medical College and Hospital from April 2025 to January 2026. One hundred patients with electrocardiographically confirmed atrial fibrillation were enrolled and followed prospectively. Baseline clinical characteristics, CHA₂DS₂-VASc scores, and biomarker levels, including high-sensitivity C-reactive protein (hs-CRP), N-terminal pro-B-type natriuretic peptide (NT-proBNP), D-dimer, and high-sensitivity cardiac troponin-I (hs-cTnI), were recorded. Stroke and systemic thromboembolic events were assessed during follow-up.
Results:
The mean age was 65.8 ± 11.4 years, and 58% were male. Eighteen patients developed ischemic stroke or systemic thromboembolic events. Patients with events had significantly higher levels of all biomarkers (p<0.001). NT-proBNP showed the highest predictive accuracy (AUC=0.89), followed by D-dimer (0.86), hs-cTnI (0.83), and hs-CRP (0.80).
Conclusion:
NT-proBNP and D-dimer significantly improved stroke risk prediction beyond conventional clinical assessment in patients with atrial fibrillation.
Recommendation:
Larger multicenter studies should validate biomarker-guided risk stratification before routine clinical implementation.
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Copyright (c) 2026 Ajitesh Kumar, Vaibhav Aditya, Ujjawal Kumar, Pankaj Hans
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