Predicting mortality after transcatheter aortic valve replacement using AI-based fully automated left atrioventricular coupling index.
Journal:
Journal of cardiovascular computed tomography
PMID:
39794233
Abstract
BACKGROUND: This study aimed to determine whether artificial intelligence (AI)-based automated assessment of left atrioventricular coupling index (LACI) can provide incremental value above other traditional risk factors for predicting mortality among patients with severe aortic stenosis (AS) undergoing coronary CT angiography (CCTA) before transcatheter aortic valve replacement (TAVR).
Authors
Keywords
Aged
Aged, 80 and over
Aortic Valve
Aortic Valve Stenosis
Artificial Intelligence
Atrial Function, Left
Automation
Computed Tomography Angiography
Coronary Angiography
Female
Humans
Male
Predictive Value of Tests
Radiographic Image Interpretation, Computer-Assisted
Retrospective Studies
Risk Assessment
Risk Factors
Severity of Illness Index
Stroke Volume
Time Factors
Transcatheter Aortic Valve Replacement
Treatment Outcome
Ventricular Function, Left