Prediction of Poor Outcome After Transcatheter Aortic Valve Replacement.

ABSTRACT:

Background

A series of models have been developed to identify patients at high risk for poor outcomes after transcatheter aortic valve replacement (TAVR) to help guide treatment choices, offer patients realistic expectations of long-term outcomes, and support decision making.

Objectives

This study examined the performance of the previously developed TAVR Poor Outcome risk models in an external dataset and explored the incremental contribution of geriatric domains to model performance.

Methods

Poor outcome after TAVR was defined as death, poor quality of life (QOL), or decline in QOL, as assessed using the Kansas City Cardiomyopathy Questionnaire. We tested 4 TAVR Poor Outcome risk models: 6-month and 1-year full and clinical (reduced) models. We examined each model's

SUBMITTER: Arnold SV 

PROVIDER: S-EPMC5119650 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature