Development and internal validation of a prediction model for hospital-acquired acute kidney injury.

ABSTRACT:

Background

Predictive models and clinical risk scores for hospital-acquired acute kidney injury (AKI) are mainly focused on critical and surgical patients. We have used the electronic clinical records from a tertiary care general hospital to develop a risk score for new-onset AKI in general inpatients that can be estimated automatically from clinical records.

Methods

A total of 47 466 patients met inclusion criteria within a 2-year period. Of these, 2385 (5.0%) developed hospital-acquired AKI. Step-wise regression modelling and Bayesian model averaging were used to develop the Madrid Acute Kidney Injury Prediction Score (MAKIPS), which contains 23 variables, all obtainable automatically from electronic clinical records at admission. Bootstrap resampling was employed for inte

SUBMITTER: Martin-Cleary C 

PROVIDER: S-EPMC7857831 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature