Related Experiment Video
Updated: Dec 23, 2025
Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
A new risk model of assessing left atrial appendage thrombus in patients with atrial fibrillation - Using multiple
Lu Chen1, Ashley Zinda2, Nicholas Rossi2
1Heart and Vascular Institute, Stamford Hospital, Stamford, CT, USA; Department of Ultrasound, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Backgrounds:
Predicting left atrial appendage thrombus (LAAT) in non-valvular atrial fibrillation (NVAF) patients need more precisely quantified risk models. In this study, we attempted to review the risk markers for LAAT and develop a simple and reliable model for LAAT prediction.
Methods:
The study included 307 patients with NVAF who were scheduled for transesophageal echocardiography (TEE) to exclude LAA thrombus before synchronized electrical cardioversion or radiofrequency ablation for atrial fibrillation (AF). We analyzed the relationship between echo, clinical parameters and the presence or absence of LAAT.
Results:
A total of 33 patients were found having LAAT (10.7%, 33/307). The age, left atrial appendage emptying velocity (LAAEV), left atrial or left atrial appendage spontaneous echocardiographic contrast (SEC), less than moderate to severe mitral regurgitation (≤mild MR), and left atrial enlargement showed association with LAAT. The multivariate logistic regression analysis revealed that LAAEV, SEC and ≤mild MR were independent risk factors of the LAAT. We used LAAEV ≤ 21.5 cm/s, SEC and ≤mild MR to construct a combined predictive model for LAAT in NVAF patients (the area under receiver operator characteristic curve: 0.88; 95% confidence interval: 0.82-0.95, P < 0.0001).
Conclusion:
Comprehensive evaluation of LAAEV, SEC, and MR with associated LAAT may help risk stratifying the NVAF patients, especially if the LAA imaging quality was suboptimal for identifying thrombus. These parameters may facilitate the decision-making process at the time of TEE.
