Development and validation of a novel combinatorial nomogram model to predict in-hospital deaths in heart failure patients.

ABSTRACT:

Background

The purpose of this study was to develop a Nomogram model to identify the risk of all-cause mortality during hospitalization in patients with heart failure (HF).

Methods

HF patients who had been registered in the Medical Information Mart for Intensive Care (MIMIC) III and IV databases were included. The primary outcome was the occurrence of all-cause mortality during hospitalization. Two Logistic Regression models (LR1 and LR2) were developed to predict in-hospital death for HF patients from the MIMIC-IV database. The MIMIC-III database were used for model validation. The area under the receiver operating characteristic curve (AUC) was used to compare the discrimination of each model. Calibration curve was used to assess the fit of each developed models. Decision

SUBMITTER: Cai D 

PROVIDER: S-EPMC10765573 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature