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Updated: Jun 25, 2026

The WATCHMAN Left Atrial Appendage Closure Device for Atrial Fibrillation
23:33

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Published on: February 28, 2012

De-risking Atrial Fibrillation: Refining Anticoagulation Decision-Making.

Navid Radfar1, Dhir Gala2, Harsh Singh2

  • 1Department of Medicine, Rutgers New Jersey Medical School, Newark, NJ, USA. nr435@njms.rutgers.edu.

American Journal of Cardiovascular Drugs : Drugs, Devices, and Other Interventions
|June 23, 2026
PubMed
Summary
This summary is machine-generated.

Traditional stroke risk scores for atrial fibrillation are insufficient. Advanced echocardiography, biomarkers, and AI can personalize stroke risk assessment, improving anticoagulation decisions for better patient care.

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Catheter Ablation in Combination With Left Atrial Appendage Closure for Atrial Fibrillation
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Published on: February 26, 2013

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Last Updated: Jun 25, 2026

The WATCHMAN Left Atrial Appendage Closure Device for Atrial Fibrillation
23:33

The WATCHMAN Left Atrial Appendage Closure Device for Atrial Fibrillation

Published on: February 28, 2012

Catheter Ablation in Combination With Left Atrial Appendage Closure for Atrial Fibrillation
28:13

Catheter Ablation in Combination With Left Atrial Appendage Closure for Atrial Fibrillation

Published on: February 26, 2013

Area of Science:

  • Cardiology
  • Biomedical Engineering

Background:

  • Current stroke risk assessment in atrial fibrillation (AF) using tools like CHA₂DS₂-VASc has limitations.
  • These tools do not fully account for individual thromboembolic risk or patient-specific factors.

Purpose of the Study:

  • To explore advanced methods for refining stroke risk stratification in AF patients.
  • To highlight the potential of multimodal data in personalizing anticoagulation therapy.

Main Methods:

  • Utilizing advanced echocardiographic markers (e.g., left atrial volume index, strain, appendage morphology).
  • Incorporating biomarkers for cardiac stress and inflammation.
  • Exploring the integration of Artificial Intelligence (AI)-enabled data.

Main Results:

  • Advanced echocardiographic markers correlate with atrial remodeling.
  • Biomarkers may enhance risk stratification accuracy.
  • Multimodal data integration offers precise de-risking strategies.

Conclusions:

  • A multimodal approach combining structural, functional, biomarker, and AI data improves stroke risk assessment in AF.
  • Personalized care models are essential for optimizing anticoagulation therapy and patient outcomes.