Assessment of acute kidney injury risk using a machine-learning guided generalized structural equation model: a cohort study.

ABSTRACT:

Background

Acute kidney injury is common in the surgical intensive care unit (ICU). It is associated with poor patient outcomes and high healthcare resource usage. This study's primary objective is to help identify which ICU patients are at high risk for acute kidney injury. Its secondary objective is to examine the effect of acute kidney injury on a patient's prognosis during and after the ICU admission.

Methods

A retrospective cohort of patients admitted to a Singaporean surgical ICU between 2015 to 2017 was collated. Patients undergoing chronic dialysis were excluded. The outcomes were occurrence of ICU acute kidney injury, hospital mortality and one-year mortality. Predictors were identified using decision tree algorithms. Confirmatory analysis was performed using a gene

SUBMITTER: Wong WEJ 

PROVIDER: S-EPMC7898752 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature