Objectives: This study aims to compare veterans and non-veterans undergoing transcatheter aortic valve replacement (TAVR) using data from the Society for Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy (STS/ACC TVT) registry.
Methods: Patients undergoing TAVR at George Washington University (GWU) and veterans treated at Washington DC Veterans Affairs Medical Center (VAMC) who underwent TAVR at GWU from 2014-2020 were included. All patients were reported in the TVT registry.
The purpose of this investigation was to characterize the CMR and clinical parameters that correlate to prosthetic valve size (PVS) determined at SAVR and develop a multi-parametric model to predict PVS. Sixty-two subjects were included. Linear/area measurements of the aortic annulus were performed on cine CMR images in systole/diastole on long/short axis (SAX) views.
View Article and Find Full Text PDFObjective: In valvular heart disease, elevated left atrial and pulmonary pressures contribute to right ventricular strain and, ultimately, right ventricle failure. Elevated pulmonary artery (PAP) and left ventricular end diastolic pressures are used as markers of right ventricle dysfunction and correlate with poor outcomes. Using cardiac magnetic resonance imaging (CMR), it is possible to directly quantify both left and right ventricular ejection function (LVEF and RVEF), and here, we compare CMR with traditional markers as outcome predictors.
View Article and Find Full Text PDFWhen interactions are identified in analysis of covariance models it becomes important to identify values of the covariates for which there are significant differences or, more generally, significant contrasts among the group mean responses. Inferential procedures that incorporate a priori order restrictions among the group mean responses would be expected to be superior to those that ignore this information. In this paper we focus on analysis of covariance models with pre-specified order restrictions on the mean response across the levels of a grouping variable when the grouping variable may interact with model covariates.
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