New predictive models of heart failure mortality using time-series measurements and ensemble models.

ABSTRACT:

Background

Morbidity and mortality rates associated with heart failure remain high. A wide variety of demographic and clinical factors as well as biomarkers are associated with increased mortality rates. Despite this, most multivariate predictive models for heart failure mortality have predictive accuracies characterized by a C-statistic (area under the receiver operating curve) of ≈0.74.

Methods and results

We analyzed data on 963 patients enrolled in the Vesnarinone Evaluation of Survival Trial (VEST), including circulating levels of 2 cytokines (tumor necrosis factor and interleukin-6) and their receptors sampled at baseline and at 8, 16, and 24 weeks. We built multivariate logistic regression models by using standard clinical variables and time-series of cytokine and cyt

SUBMITTER: Subramanian D 

PROVIDER: S-EPMC3147114 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature