Prediction models for acute kidney injury in critically ill patients: a protocol for systematic review and critical appraisal.

ABSTRACT:

Introduction

Acute kidney injury (AKI) has high morbidity and mortality in intensive care units, which can lead to chronic kidney disease, more costs and longer hospital stay. Early identification of AKI is crucial for clinical intervention. Although various risk prediction models have been developed to identify AKI, the overall predictive performance varies widely across studies. Owing to the different disease scenarios and the small number of externally validated cohorts in different prediction models, the stability and applicability of these models for AKI in critically ill patients are controversial. Moreover, there are no current risk-classification tools that are standardised for prediction of AKI in critically ill patients. The purpose of this systematic review is to map and

SUBMITTER: Wang D 

PROVIDER: S-EPMC8137185 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature