Development and External Validation of a Machine Learning Model for Prediction of Potential Transfer to the PICU.

ABSTRACT:

Objectives

Unrecognized clinical deterioration during illness requiring hospitalization is associated with high risk of mortality and long-term morbidity among children. Our objective was to develop and externally validate machine learning algorithms using electronic health records for identifying ICU transfer within 12 hours indicative of a child's condition.

Design

Observational cohort study.

Setting

Two urban, tertiary-care, academic hospitals (sites 1 and 2).

Patients

Pediatric inpatients (age <18 yr).

Interventions

None.

Measurement and main results

Our primary outcome was direct ward to ICU transfer. Using age, vital signs, and laboratory results, we derived logistic regression with regularization, restricted cubic spline regression, random

SUBMITTER: Mayampurath A 

PROVIDER: S-EPMC9262766 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature