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Updated: May 7, 2026

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

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Published on: February 26, 2013

Stroke propensity is increased under atrial fibrillation hemodynamics: a simulation study.

Hyo Won Choi¹, Jose A Navia, Ghassan S Kassab

¹Department of Biomedical Engineering, Indiana University Purdue University, Indianapolis, Indiana, United States of America.

|September 17, 2013

Summary

Atrial fibrillation (AF) increases stroke risk by promoting blood clot embolism. Computer simulations show AF

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Area of Science:

Cardiovascular physiology
Computational fluid dynamics
Stroke research

Background:

Atrial fibrillation (AF) is a common heart rhythm disorder and a significant risk factor for stroke.
AF is linked to thrombus formation and embolization, but the precise mechanisms by which hemodynamic changes in AF influence stroke risk are not fully understood.

Purpose of the Study:

To investigate how hemodynamic alterations in AF affect blood clot trajectories and stroke propensity.
To quantify the impact of AF-induced flow conditions on the potential for carotid artery embolism.

Main Methods:

Utilized computational simulations to model blood clot movement under normal and AF-related aortic flow conditions.
Assessed stroke propensity by analyzing clot trajectories for various clot properties (diameter, ejection speed).

Main Results:

Clot trajectory and stroke propensity are significantly influenced by both clot characteristics and hemodynamic waveforms.
Simulations predicted up to a 60% greater stroke propensity in the carotid artery under AF conditions compared to normal rhythm.
Reduced cardiac output and shorter cycle length in AF were identified as key factors increasing carotid embolism risk.

Conclusions:

Hemodynamic changes associated with atrial fibrillation can substantially elevate the risk of carotid artery embolism and subsequent stroke.
These findings highlight the need for patient-specific stroke risk assessments in individuals with AF.
Computational modeling provides valuable insights into the mechanisms underlying stroke propensity in AF.