Ontology highlight
ABSTRACT: Aim
To identify predictors for in-hospital mortality in patients with metastatic cancer in intensive care units (ICUs) and established a prediction model for in-hospital mortality in those patients.Methods
In this cohort study, the data of 2,462 patients with metastatic cancer in ICUs were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Least absolute shrinkage and selection operator (LASSO) regression analysis was applied to identify the predictors for in-hospital mortality in metastatic cancer patients. Participants were randomly divided into the training set (n = 1,723) and the testing set (n = 739). Patients with metastatic cancer in ICUs from MIMIC-IV were used as the validation set (n = 1,726). The predicti
SUBMITTER: Wu M
PROVIDER: S-EPMC9922743 | biostudies-literature | 2023
REPOSITORIES: biostudies-literature