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Assessment of Vascular Function in Patients With Chronic Kidney Disease
08:50

Assessment of Vascular Function in Patients With Chronic Kidney Disease

Published on: June 16, 2014

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Machine learning analysis of serum biomarkers for cardiovascular risk assessment in chronic kidney disease

Carles Forné1,2, Serafi Cambray3, Marcelino Bermudez-Lopez3

  • 1Biostatistics Unit, Institute for Biomedical Research Dr. Pifarré Foundation, IRBLleida, Lleida, Spain.

Clinical Kidney Journal
|September 9, 2020
PubMed

Insights

This study found that four specific biomarkers can help predict cardiovascular events in chronic kidney disease (CKD) patients, improving risk assessment for those at high risk.

Area of Science:

  • Nephrology
  • Cardiology
  • Biomarker Discovery

Background:

  • Chronic kidney disease (CKD) patients face a high risk of atherosclerosis and cardiovascular events (CVEs).
  • Existing biomarkers for CVEs lack combined effectiveness in CKD risk stratification.
  • The NEFRONA study investigated cardiovascular risk in CKD patients.

Purpose of the Study:

  • To analyze the combined ability of 19 biomarkers in predicting CVEs over 4 years in CKD patients without prior CVEs.
  • To assess the added value of these biomarkers beyond classical clinical parameters for cardiovascular risk estimation.

Main Methods:

  • Quantified 19 biomarkers in 1366 CKD patients.
  • Utilized random survival forest (RSF) analysis to rank biomarker predictive ability.
  • Employed Fine and Gray (FG) regression models with competing risks (non-cardiovascular death, kidney transplant).

Main Results:

  • RSF identified several relevant biomarkers for CVE prediction.
  • High levels of osteopontin, osteoprotegerin, MMP-9, and VEGF marginally improved risk prediction (C-index 0.744 vs. 0.723).
  • Biomarker assessment showed potential for improved risk estimates in diabetic CKD patients on medication.

Conclusions:

  • Serum determination of four specific biomarkers can enhance cardiovascular risk prediction in CKD.
  • These biomarkers offer improved risk stratification, particularly for high-risk individuals.
Abstract

Keywords:
biomarkerscardiovascular riskcohort studycompeting risksrandom forest

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