Mortality Risk Factors in Pediatric Onco-Critical Care Patients and Machine Learning Derived Early Onco-Critical Care Phenotypes in a Retrospective Cohort.

ABSTRACT:

Objectives

To use supervised and unsupervised statistical methodology to determine risk factors associated with mortality in critically ill pediatric oncology patients to identify patient phenotypes of interest for future prospective study.

Design

This retrospective cohort study included nonsurgical pediatric critical care admissions from January 2017 to December 2018. We determined the prevalence of multiple organ failure (MOF), ICU mortality, and associated factors. Consensus k-means clustering analysis was performed using 35 bedside admission variables for early, onco-critical care phenotype development.

Setting

Single critical care unit in a subspeciality pediatric hospital.

Intervention

None.

Patients

There were 364 critical care admissions i

SUBMITTER: Flerlage T 

PROVIDER: S-EPMC10538916 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature