A Machine Learning Classifier Improves Mortality Prediction Compared With Pediatric Logistic Organ Dysfunction-2 Score: Model Development and Validation.

ABSTRACT:

Objectives

To determine whether machine learning algorithms can better predict PICU mortality than the Pediatric Logistic Organ Dysfunction-2 score.

Design

Retrospective study.

Setting

Quaternary care medical-surgical PICU.

Patients

All patients admitted to the PICU from 2013 to 2019.

Interventions

None.

Measurements and main results

We investigated the performance of various machine learning algorithms using the same variables used to calculate the Pediatric Logistic Organ Dysfunction-2 score to predict PICU mortality. We used 10,194 patient records from 2013 to 2017 for training and 4,043 patient records from 2018 to 2019 as a holdout validation cohort. Mortality rate was 3.0% in the training cohort and 3.4% in the validation cohort. The best pe

SUBMITTER: Prince RD 

PROVIDER: S-EPMC8133049 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature