Abstract 126: A Simple Classification of the Left Atrial Appendage Morphology Based on Stroke Risk: The LAA H/L Classification System

Stroke ◽  
2019 ◽  
Vol 50 (Suppl_1) ◽  
Author(s):  
Shadi Yaghi ◽  
Andrew Chang ◽  
Hooman Kamel ◽  
Karen Furie ◽  
Mitchell S Elkind ◽  
...  
Keyword(s):  
Classification System ◽  
Left Atrial ◽  
Stroke Risk ◽  
Left Atrial Appendage ◽  
Atrial Appendage ◽  
Simple Classification

Abstract WP260: The Left Atrial Appendage Morphology Improves Prediction of Appendage Stagnant Flow and Stroke Risk in Patients With Atrial Fibrillation Using a Simple Classification System

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Shadi Yaghi ◽  
Andrew Chang ◽  
Gian Ignacio ◽  
Erica Scher ◽  
Nikhil Panda ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Flow Velocity ◽  
Primary Endpoint ◽  
Classification System ◽  
Left Atrial ◽  
Left Atrial Appendage ◽  
Current System ◽  
Classification Systems ◽  
Atrial Appendage ◽  
Simple Classification

Background and Purpose: Previously we proposed a simple classification system of the left atrial appendage (LAA) morphology, with low risk (LAA-L) defined as one lobe with an acute angle bend arising from the proximal or middle portion and high risk (LAA-H) defined as all other morphologies. We aim to determine the association between LAA morphology (using both classification systems), LAA flow velocity, and stroke rates. Methods: We analyzed consecutive patients with atrial fibrillation (AF) selected for ablation who underwent cardiac CT angiography and transesophageal echocardiogram. The primary correlates were LAA-H and non-chicken wing (NCW) LAA morphology. The primary outcome was the composite endpoint of history of ischemic stroke/TIA or non-lacunar infarct on neuroimaging. Adjusting for CHADS2Vasc score, multivariable models were used to determine associations between LAA morphology and composite outcomes. Results: We identified 379 patients; the primary endpoint occurred in 32/379 patients (8.4%). LAA-H (adjusted OR 3.63, 95% CI 1.44-9.14) and NCW LAA morphology (adjusted OR 2.52, 95% CI 1.15-5.53) were associated with the primary endpoint. LAA flow velocity ≤20 cm/s was more common in LAA-H vs. LAA-L (9.6% vs. 2.8%, p = 0.019), but not in NCW vs. CW LAA morphology (9.7% vs. 3.7%, p = 0.054). Conclusion: The LAA H/L morphological classification system may be superior to the current system in risk stratifying patients with AF and correlates better with impaired LAA flow dynamics.

Stroke Prophylaxis by Percutaneous Closure of Patent Foramen Ovale and Left Atrial Appendage

2011 ◽  
Vol 6 (1) ◽  
pp. 67
Author(s):  
Antonio L Bartorelli ◽  
Claudio Tondo ◽  
◽  
Keyword(s):  
Left Atrial ◽  
Patent Foramen Ovale ◽  
Stroke Risk ◽  
Left Atrial Appendage ◽  
Cryptogenic Stroke ◽  
Atrial Appendage ◽  
Foramen Ovale ◽  
Percutaneous Procedures ◽  
Cerebrovascular Events

Innovative percutaneous procedures for stroke prevention have emerged in the last two decades. Transcatheter closure of the patent foramen ovale (PFO) is performed in patients who suffered a cryptogenic stroke or a transient ischaemic attach (TIA) in order to prevent recurrence of thromboembolic events. Percutaneous occlusion of the left atrial appendage (LAA) has been introduced to reduce stroke risk in patients with atrial fibrillation (AF). The role of PFO and LAA in the occurrence of cerebrovascular events and the interventional device-based therapies to occlude the PFO and LAA are discussed.

scholarly journals P3854Analysis of stroke risk based on morphological parameters of the left atrial appendage derived from 3D angiography

2018 ◽  
Vol 39 (suppl_1) ◽  
Author(s):  
E Silva Garcia ◽  
K Iliodromitis ◽  
P Geelen ◽  
O Camara ◽  
T De Potter
Keyword(s):  
Left Atrial ◽  
Stroke Risk ◽  
Left Atrial Appendage ◽  
Atrial Appendage ◽  
Morphological Parameters ◽  
3D Angiography

Classification of Left Atrial Appendage Morphology Using Deep Learning

2020 ◽  
Author(s):  
Mikayle A. Holm ◽  
Alex Deakyne ◽  
Erik Gaasedelen ◽  
Weston Upchurch ◽  
Paul A. Iaizzo
Keyword(s):  
Left Atrial ◽  
Left Atrial Appendage ◽  
Blood Clot ◽  
3D Models ◽  
Atrial Appendage ◽  
Blood Clots ◽  
Mri Scans ◽  
2D Images ◽  
Trained Network

Abstract Atrial fibrillation, a common cardiac arrhythmia, can lead to blood clots in the left atrial appendage (LAA) of the heart, increasing the risk of stroke. Understanding the LAA morphology can indicate the likelihood of a blood clot. Therefore, a classification convolutional neural network was implemented to predict the LAA morphology. Using 2D images of 3D models created from MRI scans of fixed human hearts and a pre-trained network, an 8.7% error rate was achieved. The network can be improved with more data or expanded to classify the LAA from the automatically segmented DICOM datasets and measure the LAA ostia.

scholarly journals The predictive value of a concise classification of left atrial appendage morphology to thrombosis in non‐valvular atrial fibrillation patients

2020 ◽  
Vol 43 (7) ◽  
pp. 789-795 ◽  
Author(s):  
Jionghong He ◽  
Zenan Fu ◽  
Long Yang ◽  
Wei Liu ◽  
Ye Tian ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Predictive Value ◽  
Left Atrial ◽  
Left Atrial Appendage ◽  
Atrial Appendage
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