Severe acute kidney injury predicting model based on transcontinental databases: a single-centre prospective study.

ABSTRACT:

Objectives

There are many studies of acute kidney injury (AKI) diagnosis models lack of external validation and prospective validation. We constructed the models using three databases to predict severe AKI within 48 hours in intensive care unit (ICU) patients.

Design

A retrospective and prospective cohort study.

Setting

We studied critically ill patients in our database (SHZJU-ICU) and two other public databases, the Medical Information Mart for Intensive Care (MIMIC) and AmsterdamUMC databases, including basic demographics, vital signs and laboratory results. We predicted the diagnosis of severe AKI in patients in the next 48 hours using machine-learning algorithms with the three databases. Then, we carried out real-time severe AKI prediction in the prospective valid

SUBMITTER: Liang Q 

PROVIDER: S-EPMC8896056 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature