Establishment and validation of a prediction nomogram for heart failure risk in patients with acute myocardial infarction during hospitalization.

ABSTRACT:

Background

Acute myocardial infarction (AMI) with consequent heart failure is one of the leading causes of death in humans. The aim of this study was to develop a prediction model to identify heart failure risk in patients with AMI during hospitalization.

Methods

The data on hospitalized patients with AMI were retrospectively collected and divided randomly into modeling and validation groups at a ratio of 7:3. In the modeling group, the independent risk factors for heart failure during hospitalization were obtained to establish a logistic prediction model, and a nomogram was constructed. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the predictive performance and clinical value. Machine learning

SUBMITTER: Chen S 

PROVIDER: S-EPMC10726532 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature