Prediction and Risk Stratification of Cardiovascular Disease in Diabetic Kidney Disease Patients.

ABSTRACT:

Background

Diabetic kidney disease (DKD) patients are facing an extremely high risk of cardiovascular disease (CVD), which is a major cause of death for DKD patients. We aimed to build a deep learning model to predict CVD risk among DKD patients and perform risk stratifying, which could help them perform early intervention and improve personal health management.

Methods

A retrospective cohort study was conducted to assess the risk of the occurrence of composite cardiovascular disease, which includes coronary heart disease, cerebrovascular diseases, congestive heart failure, and peripheral artery disease, in DKD patients. A least absolute shrinkage and selection operator (LASSO) regression was used to perform the variable selection. A deep learning-based survival model called

SUBMITTER: Ren J 

PROVIDER: S-EPMC9263287 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature