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Updated: Apr 10, 2026
Assessment of Vascular Function in Patients With Chronic Kidney Disease
Published on: June 16, 2014
Do biologic markers predict cardiovascular end points in diabetic end-stage renal disease? A prospective longitudinal
George P Bayliss1, Larry A Weinrauch2, Ray E Gleason3
1Division of Kidney Diseases and Hypertension , Rhode Island Hospital , Providence , RI , USA ; Department of Medicine, Alpert School of Medicine , Brown University , Providence , RI , USA.
Insights
Biomarkers for inflammation, oxidative stress, and hemostasis did not improve cardiovascular event prediction in diabetic patients on renal replacement therapy. Only plasminogen activator inhibitor (PAI) showed potential, but further research is needed.
Area of Science:
- Nephrology
- Cardiology
- Clinical Chemistry
Background:
- Diabetic patients on hemodialysis face high cardiovascular disease mortality risk.
- Biomarkers of inflammation, oxidative stress, and hemostasis may enhance cardiovascular event prediction.
- Predictive information is crucial for renal transplant evaluation in this high-risk group.
Purpose of the Study:
- To investigate the utility of biologic markers in predicting cardiovascular event (CVE)-free survival in diabetic patients undergoing renal replacement therapy (RRT).
- To assess if inflammation, oxidative stress, and hemostasis markers add predictive value to clinical information.
Main Methods:
- Prospective study of 150 diabetic and 27 non-diabetic RRT patients.
- Follow-up for cardiovascular events (CVEs) and mortality.
- Measurement of biologic markers: Il-6, C-reactive protein, fibrinogen, PAI, fibrinolytic activity, vWF, platelet-selectin, viscosity, advanced glycated end products, and anti-oxidized LDL.
Main Results:
- High prevalence of prior cardiovascular events in all groups (51.3% DM1, 54.0% DM2, 25.9% DM0).
- Subsequent CVEs occurred in 31.6% DM1, 45.9% DM2, and 11.1% DM0 patients.
- All mean biomarker levels at baseline were significantly abnormal (P < 0.05).
Conclusions:
- Biologic marker levels, except for PAI, did not improve the clinical prediction of cardiovascular events in this RRT population.
- Further investigation into PAI's role may be warranted.
- Current biomarkers have limited utility for predicting outcomes in diabetic RRT patients.
Background:
Diabetic patients on hemodialysis are at high risk of death from cardiovascular disease, and research has suggested that various biologic markers of inflammation, oxidative stress and hemostasis may give added value to clinical information for predicting cardiovascular event (CVE)-free survival. This information could be particularly important in evaluating this population for renal transplant, given the scarcity of organs. We hypothesized that in diabetic patients undergoing renal replacement therapy (RRT) these biologic markers would prove useful in predicting event-free follow-up in a prospective study.
Methods:
One hundred and fifty diabetic (76 type 1, 74 type 2) and 27 non-diabetic stable RRT patients were followed for 0.04-13.69 years for CVE (myocardial infarction, coronary arterial intervention, peripheral arterial bypass or amputation, cerebrovascular accident or carotid artery intervention), cardiac and all-cause mortality. Measured biologic markers of inflammation included the following: Il-6, C reactive protein, fibrinogen; of hemostasis: fibrinogen, plasminogen activator inhibitor (PAI), fibrinolytic activity, von Willebrand factor VII (vWF), platelet-selectin, viscosity and of oxidative stress: advanced glycated end products and antibody to oxidized low-density lipoprotein. For each, upper versus lower tertiles were compared for duration of event-free follow-up.
Results:
Cardiovascular events prior to study entry occurred in 51.3% of DM1, 54.0% of DM2 and 25.9% of DM0 patients. Subsequent cardiovascular events were noted in 31.6% of DM1, 45.9% of DM2 and 11.1% of DM0 patients. All mean levels of biologic markers at baseline were abnormal (P < 0.05).
Conclusions:
In this RRT population, all biologic marker levels except PAI did not improve clinical prediction of events.
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