Machine Learning-Based Prediction Model for ICU Mortality After Continuous Renal Replacement Therapy Initiation in Children.

ABSTRACT:

Background

Continuous renal replacement therapy (CRRT) is the favored renal replacement therapy in critically ill patients. Predicting clinical outcomes for CRRT patients is difficult due to population heterogeneity, varying clinical practices, and limited sample sizes.

Objective

We aimed to predict survival to ICUs and hospital discharge in children and young adults receiving CRRT using machine learning (ML) techniques.

Derivation cohort

Patients less than 25 years of age receiving CRRT for acute kidney injury and/or volume overload from 2015 to 2021 (80%).

Validation cohort

Internal validation occurred in a testing group of patients from the dataset (20%).

Prediction model

Retrospective international multicenter study utilizing an 80/20 training and te

SUBMITTER: Thadani S 

PROVIDER: S-EPMC11654792 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature