The development and validation of a prediction model for post-AKI outcomes of pediatric inpatients.

ABSTRACT:

Background

Acute kidney injury (AKI) is common in hospitalized children. A post-AKI outcomes prediction model is important for the early detection of important clinical outcomes associated with AKI so that early management of pediatric AKI patients can be initiated.

Methods

Three retrospective cohorts were set up based on two pediatric hospitals in China, in which 8205 children suffered AKI during hospitalization. Two clinical outcomes were evaluated, i.e. hospital mortality and dialysis within 28 days after AKI occurrence. A Genetic Algorithm was used for feature selection, and a Random Forest model was built to predict clinical outcomes. Subsequently, a temporal validation set and an external validation set were used to evaluate the performance of the prediction model. Fin

SUBMITTER: Zhang C 

PROVIDER: S-EPMC11843026 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature