Development and validation of outcome prediction models for acute kidney injury patients undergoing continuous renal replacement therapy.

ABSTRACT:

Object

This study aimed to develop and validate a set of practical predictive tools that reliably estimate the 28-day prognosis of acute kidney injury patients undergoing continuous renal replacement therapy.

Methods

The clinical data of acute kidney injury patients undergoing continuous renal replacement therapy were extracted from the Medical Information Mart for Intensive Care IV database with structured query language and used as the development cohort. An all-subset regression was used for the model screening. Predictive models were constructed via a logistic regression, and external validation of the models was performed using independent external data.

Results

Clinical prediction models were developed with clinical data from 1,148 patients and validated

SUBMITTER: Li B 

PROVIDER: S-EPMC9433572 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature