Prediction of prognosis in elderly patients with chronic heart failure based on random survival forest.

ABSTRACT:

Background

There is a lack of tools to identify the risk of poor prognosis in elderly patients with chronic heart failure (CHF). This study aimed to develop a random survival forest (RSF) model to predict the prognosis of elderly CHF patients.

Methods

The primary endpoint of this was all-cause mortality. The secondary endpoint was the combined outcome of unplanned readmissions and all-cause mortality. Patients were divided into a training set and a test set at a ratio of 7:3. We established and compared the performance of the RSF model with that of the New York Heart Association (NYHA) functional classes, left ventricular ejection fraction (LVEF) and B-type natriuretic peptide (BNP) level in evaluating the prognosis of elderly CHF patients. Harrell's C-index, decision curve

SUBMITTER: Song X 

PROVIDER: S-EPMC12446311 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature