CKD Progression Prediction in a Diverse US Population: A Machine-Learning Model

ABSTRACT:

Rationale & Objective

Chronic kidney disease (CKD) is a major cause of morbidity and mortality. To date, there are no widely used machine-learning models that can predict progressive CKD across the entire disease spectrum, including the earliest stages. The objective of this study was to use readily available demographic and laboratory data from Sonic Healthcare USA laboratories to train and test the performance of machine learning-based predictive risk models for CKD progression.

Study Design

Retrospective observational study

Setting & Participants

The study population was composed of deidentified laboratory information services data procured from a large US outpatient laboratory network. The retrospective data set included 110,264 adult patients over a 5-year p

SUBMITTER:  

PROVIDER: S-EPMC10457449 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature