Abstract
Introduction: Severe aortic valve stenosis (AS) is a progressive and insidious disease that causes rapid progression of debilitating symptoms. There are currently two treatment options that reduce mortality: surgical aortic valve replacement (SAVR) and transcatheter aortic valve replacement (TAVR). There are limited reports with a primary focus of symptom improvement following TAVR.The purpose of this study is to examine the AS-related symptoms over time, comparing baseline (pre-TAVR) to post-TAVR symptoms, using both objective and subjective reporting. Methods: This is a retrospective chart review, with descriptive and correlational aspects. It will also be a determination of feasibility for a larger study. A measure of both subjective and objective report of symptoms pre-TAVR and post-TAVR is a component of the charts. The objective measure of symptoms will be the New York Heart Association Functional Classification (NYHA), reported by providers. The shortened version of the Kansas City Cardiomyopathy Questionnaire (KCCQ-12) will be used to measure subjective symptoms; this survey is completed by patients pre-TAVR and post-TAVR at one month. A sample size of 80 charts from a single site will be used. Descriptive analyses will be used to describe the sample. Chi-square (NYHA class) and dependent t-tests (KCCQ-12 scores) will be used to determine whether changes in symptoms over time are significant. Spearman rank-order will be used to observe for associations between NYHA and KCCQ-12. Correlational statistics (chi-square and Pearson’s) will be used to investigate associations between patient characteristics and symptom scores at one month following TAVR. Results: Preliminary data shows trends towards improvement in self-reported symptoms and provider observed functional classification status post TAVR. Statistical analysis to support these findings is forthcoming. Conclusions: In this feasibility study, preliminary data supports improvement in quality signals status post TAVR. Further large-scale studies are needed to validate these findings.
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