Back to Search Start Over

Evaluating the Clinical Utility of Left Ventricular Strains in Severe AS: A Pilot Study with Feature-Tracking Cardiac Magnetic Resonance.

Authors :
Cionca, Carmen
Zlibut, Alexandru
Agoston, Renata
Agoston-Coldea, Lucia
Orzan, Rares Ilie
Mocan, Teodora
Source :
Biomedicines; Sep2024, Vol. 12 Issue 9, p2104, 13p
Publication Year :
2024

Abstract

Background: Aortic valve stenosis (AS) is the most common degenerative valvular heart disease, significantly impacting the outcome. Current guidelines recommend valve replacement only for symptomatic patients, but advanced cardiovascular imaging, particularly cardiac magnetic resonance (CMR), may refine these recommendations. Feature-tracking CMR (FT-CMR) effectively assesses left ventricular (LV) strain and shows promise in predicting major adverse cardiovascular events (MACEs), though data on AS are limited. This study explored the role of CMR-derived LV strain in predicting MACEs occurrence in patients with severe AS. Method: We prospectively assessed 84 patients with severe AS and 84 matched controls. Global longitudinal (GLS), circumferential (GCS), and radial strain (GRS) were evaluated using FT-CMR. A composite endpoint—cardiac death, ventricular tachyarrhythmias, and heart failure hospitalization—was analyzed over a median follow-up of 31 months. Results: GLS was considerably reduced in AS patients (−15.8% vs. −19.7%, p < 0.001) and significantly predicted MACEs (HR = 1.24, p = 0.002) after adjusting for LVEF, 6 min walk distance, native T1, and late gadolinium enhancement. This underscores GLS's unique and robust predictive capability for MACEs in severe AS patients. Kaplan–Meier curves and ROC analysis both showed that GLS had the highest predictive performance for MACEs, with an AUC of 0.857. Conclusions: GLS provided independent incremental predictive value for outcome. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22279059
Volume :
12
Issue :
9
Database :
Complementary Index
Journal :
Biomedicines
Publication Type :
Academic Journal
Accession number :
180010523
Full Text :
https://doi.org/10.3390/biomedicines12092104