Artigo Revisado por pares

Aortic valve calcium score as a predictor for outcome after TAVI using the CoreValve revalving system

2011; Elsevier BV; Volume: 166; Issue: 3 Linguagem: Inglês

10.1016/j.ijcard.2011.11.091

ISSN

1874-1754

Autores

Alexander Leber, Markus Kasel, Thomas Ischinger, Ulrich Ebersberger, Diethmar Antoni, Martin Schmidt, G. Rieß, Vivian Renz, Armin Huber, Thomas Helmberger, Ellen Hoffmann,

Tópico(s)

Cardiac Imaging and Diagnostics

Resumo

Background TAVI is a novel treatment option for patients at too high risk for surgery. Risk scores for surgical valve replacement failed to accurately predict outcomes after TAVI and alternative risk parameters are lacking so far. Objective We evaluated the CT-derived aortic valve calcification score as a predictor for outcome during and after TAVI. Methods Transfemoral TAVI using the CoreValve device was performed in 68 patients, in whom the aortic valve calcium score was determined from preprocedural 64-sclice ECG gated CT-scans. Results 30-day MACE rate (death, stroke, MI) was 10.3%, 1-year mortality was 11.8%. Using linear regression analysis the aortic valve calcium score was the only significant predictor for 30-day MACE and for 1-year mortality and was also associated with the incidence and severity of post procedural aortic regurgitation (r=0.33, p 750 had a significant lower 1-year survival rate compared to patients with scores <750 (58% vs. 98%, p<0.05). The aortic valve calcium score is also inversely associated with the absolute improvement of NYHA-class after TAVI (regression coefficient=−0.43, p<0.02). Conclusion The degree of aortic valve calcification is associated with post procedural aortic regurgitation, procedural complications, 1-year mortality and with the degree of functional improvement of patients who underwent TAVI using the CoreValve device. Due to the fact that the aortic valve calcium score can be determined from CT-datasets that are used for preprocedural planning, this parameter may be incorporated in the general work up and may be used for risk stratification and patient selection.

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