Impact of aortic valve calcification severity and impaired left ventricular function on 3-year results of patients undergoing transcatheter aortic valve replacement.

Autor: Koos R; Department of Cardiology, University Hospital RWTH Aachen, RWTH University Aachen, Pauwelsstrasse 30, 52074, Aachen, Germany, rkoos@ukaachen.de., Reinartz S, Mahnken AH, Herpertz R, Lotfi S, Autschbach R, Marx N, Hoffmann R
Jazyk: angličtina
Zdroj: European radiology [Eur Radiol] 2013 Dec; Vol. 23 (12), pp. 3253-61. Date of Electronic Publication: 2013 Jul 03.
DOI: 10.1007/s00330-013-2961-4
Abstrakt: Objectives: To evaluate clinical pre-interventional predictors of 3-year outcome and mortality in high-risk patients with severe aortic valve stenosis treated with transcatheter aortic valve implantation (TAVI).
Methods: Among 367 patients included in the Aachen TAVI registry, 76 patients with baseline dual-source computed tomography (DSCT) for the quantification of aortic valve calcification (AVC) and a 3-year follow-up were identified.
Results: Survival at 30 days was 91 %, and it was 75 %, 66 % and 64 % at 1, 2 years and 3 years, respectively. Non-survivors at 3 years showed a significantly higher Agatston AVC score (2,854 ± 1,651) than survivors (1,854 ± 961, P = 0.007). Multivariate analysis including age, logistic EuroScore, glomerular filtration rate, Agatston AVC score, ejection fraction < 40 %, NYHA class, baseline medication, chronic lung disease and aortic regurgitation revealed that only the Agatston AVC score (P = 0.03) and impaired left ventricular function (P = 0.001) was significantly associated with mortality. Patients with Agatston AVC scores >2,000 had a significantly lower 3-year survival rate compared with patients with scores <2,000 (47 % vs 79 %, P = 0.004).
Conclusions: In patients referred for TAVI, aortic valve calcification severity and impaired left ventricular function may serve as a predictor of long-term mortality. Therefore, AVC scores easily determined from pre-procedural CT datasets may be used for patient risk stratification.
Databáze: MEDLINE
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