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Published on: April 8, 2013
Redefining cardiac damage staging in aortic stenosis: the value of GLS and RVAc
Eva Gutierrez-Ortiz1, Carmen Olmos1, Irene Carrión-Sanchez1
1Instituto Cardiovascular, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdSSC), Calle Profesor Martín Lagos S/N, Madrid 28040, Spain.
Aims:
Cardiac damage staging has been postulated as a prognostic tool in patients undergoing transcatheter aortic valve replacement (TAVR). The aims of our study are (i) to validate cardiac damage staging systems previously described to stratify patients with aortic stenosis (AS), (ii) to identify independent risk factors for 1-year mortality in patients with severe AS undergoing TAVR, and (iii) to develop a novel staging model and compare its predictive performance to that of the above mentioned.
Methods And Results:
Patients undergoing TAVR from 2017 to 2021 were included in a single-centre prospective registry. Transthoracic echocardiography was performed in all patients before TAVR. Logistic and Cox's regression analysis were used to identify predictors of 1-year all-cause mortality. In addition, patients were classified based on previously published cardiac damage staging systems, and the predictive performance of the different scores was measured.Four hundred and ninety-six patients (mean age 82.1 ± 5.9 years, 53% female) were included. Mitral regurgitation (MR), left ventricle global longitudinal strain (LV-GLS) and right ventricular-arterial coupling (RVAc) were independent predictors of all-cause 1-year mortality. A new classification system with four different stages was developed using LV-GLS, MR, and RVAc. The area under the receiver operating characteristic curve was 0.66 (95% confidence interval 0.63-0.76), and its predictive performance was superior compared with the previously published systems (P < 0.001).
Conclusion:
Cardiac damage staging might have an important role in patients' selection and better timing for TAVR. A model that includes LV-GLS, MR, and RVAc may help to improve prognostic stratification and contribute to better selection of patients undergoing TAVR.
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