Development and deployment of a nationwide predictive model for chronic kidney disease progression in diabetic patients.

ABSTRACT:

Aim

Chronic kidney disease (CKD) is a major complication of diabetes and a significant disease burden on the healthcare system. The aim of this work was to apply a predictive model to identify high-risk patients in the early stages of CKD as a means to provide early intervention to avert or delay kidney function deterioration.

Materials and methods

Using the data from the National Diabetes Database in Singapore, we applied a machine-learning algorithm to develop a predictive model for CKD progression in diabetic patients and to deploy the model nationwide.

Results

Our model was rigorously validated. It outperformed existing models and clinician predictions. The area under the receiver operating characteristic curve (AUC) of our model is 0.88, with the 95% confidence i

SUBMITTER: Fu Z 

PROVIDER: S-EPMC10800693 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature