A Bayesian Model to Predict Right Ventricular Failure Following Left Ventricular Assist Device Therapy.

ABSTRACT:

Objectives

This study investigates the use of a Bayesian statistical model to address the limited predictive capacity of existing risk scores derived from multivariate analyses. This is based on the hypothesis that it is necessary to consider the interrelationships and conditional probabilities among independent variables to achieve sufficient statistical accuracy.

Background

Right ventricular failure (RVF) continues to be a major adverse event following left ventricular assist device (LVAD) implantation.

Methods

Data used for this study were derived from 10,909 adult patients from the Inter-Agency Registry for Mechanically Assisted Circulatory Support (INTERMACS) who had a primary LVAD implanted between December 2006 and March 2014. An initial set of 176 pre-implanta

SUBMITTER: Loghmanpour NA 

PROVIDER: S-EPMC5010475 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature