Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
August 17, 2025Open Access

Machine Learning-Driven Evaluation of Lipid Markers for Cardiovascular Risk in Chronic Kidney Disease Patients: An Analysis from NHANES

View Full Paper
Ask AI
Bookmark
Share

Authors

GWGen WenFZFeifei ZhangHXHao Xiao

Discussion

Loading...

Member takes

Overview

Analysis identifies lipid markers as CVD risk predictors in CKD patients, suggesting machine learning methods enhance predictive accuracy.

Key Points

  • In CKD patients, TC, LDL-C, and ApoB serve as independent predictors of cardiovascular disease risk, enhancing risk stratification.
  • The study evaluated 2,696 participants, revealing that LDL-C emerged as the best indicator of cardiovascular risk among lipid markers.
  • Analysis employed multivariate logistic regression and machine learning models to assess relationships between various lipid markers and cardiovascular disease.
  • Integration of lipid markers into predictive models may facilitate timely identification of CKD patients at high cardiovascular risk.

Cite This Study

Wen et al. (2025) studied this question.

synapsesocial.com/papers/68af76bf7567bf4f94feff50https://doi.org/10.21203/rs.3.rs-7078587/v1
View Full Paper
Ask AI
Bookmark
Share