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Protein-Bound Uremic Toxin Profiling as a Tool to Optimize Hemodialysis

AIM: We studied various hemodialysis strategies for the removal of protein-bound solutes, which are associated with cardiovascular damage. METHODS: This study included 10 patients on standard (3x4h/week) high-flux hemodialysis. Blood was collected at the dialyzer inlet and outlet at several time poi...

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Autores principales: Eloot, Sunny, Schneditz, Daniel, Cornelis, Tom, Van Biesen, Wim, Glorieux, Griet, Dhondt, Annemie, Kooman, Jeroen, Vanholder, Raymond
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4723122/
https://www.ncbi.nlm.nih.gov/pubmed/26799394
http://dx.doi.org/10.1371/journal.pone.0147159
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author Eloot, Sunny
Schneditz, Daniel
Cornelis, Tom
Van Biesen, Wim
Glorieux, Griet
Dhondt, Annemie
Kooman, Jeroen
Vanholder, Raymond
author_facet Eloot, Sunny
Schneditz, Daniel
Cornelis, Tom
Van Biesen, Wim
Glorieux, Griet
Dhondt, Annemie
Kooman, Jeroen
Vanholder, Raymond
author_sort Eloot, Sunny
collection PubMed
description AIM: We studied various hemodialysis strategies for the removal of protein-bound solutes, which are associated with cardiovascular damage. METHODS: This study included 10 patients on standard (3x4h/week) high-flux hemodialysis. Blood was collected at the dialyzer inlet and outlet at several time points during a midweek session. Total and free concentration of several protein-bound solutes was determined as well as urea concentration. Per solute, a two-compartment kinetic model was fitted to the measured concentrations, estimating plasmatic volume (V(1)), total distribution volume (V(tot)) and intercompartment clearance (K(21)). This calibrated model was then used to calculate which hemodialysis strategy offers optimal removal. Our own in vivo data, with the strategy variables entered into the mathematical simulations, was then validated against independent data from two other clinical studies. RESULTS: Dialyzer clearance K, V(1) and V(tot) correlated inversely with percentage of protein binding. All Ks were different from each other. Of all protein-bound solutes, K(21)was 2.7–5.3 times lower than that of urea. Longer and/or more frequent dialysis that processed the same amount of blood per week as standard 3x4h dialysis at 300mL/min blood flow showed no difference in removal of strongly bound solutes. However, longer and/or more frequent dialysis strategies that processed more blood per week than standard dialysis were markedly more adequate. These conclusions were successfully validated. CONCLUSION: When blood and dialysate flow per unit of time and type of hemodialyzer are kept the same, increasing the amount of processed blood per week by increasing frequency and/or duration of the sessions distinctly increases removal.
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spelling pubmed-47231222016-01-30 Protein-Bound Uremic Toxin Profiling as a Tool to Optimize Hemodialysis Eloot, Sunny Schneditz, Daniel Cornelis, Tom Van Biesen, Wim Glorieux, Griet Dhondt, Annemie Kooman, Jeroen Vanholder, Raymond PLoS One Research Article AIM: We studied various hemodialysis strategies for the removal of protein-bound solutes, which are associated with cardiovascular damage. METHODS: This study included 10 patients on standard (3x4h/week) high-flux hemodialysis. Blood was collected at the dialyzer inlet and outlet at several time points during a midweek session. Total and free concentration of several protein-bound solutes was determined as well as urea concentration. Per solute, a two-compartment kinetic model was fitted to the measured concentrations, estimating plasmatic volume (V(1)), total distribution volume (V(tot)) and intercompartment clearance (K(21)). This calibrated model was then used to calculate which hemodialysis strategy offers optimal removal. Our own in vivo data, with the strategy variables entered into the mathematical simulations, was then validated against independent data from two other clinical studies. RESULTS: Dialyzer clearance K, V(1) and V(tot) correlated inversely with percentage of protein binding. All Ks were different from each other. Of all protein-bound solutes, K(21)was 2.7–5.3 times lower than that of urea. Longer and/or more frequent dialysis that processed the same amount of blood per week as standard 3x4h dialysis at 300mL/min blood flow showed no difference in removal of strongly bound solutes. However, longer and/or more frequent dialysis strategies that processed more blood per week than standard dialysis were markedly more adequate. These conclusions were successfully validated. CONCLUSION: When blood and dialysate flow per unit of time and type of hemodialyzer are kept the same, increasing the amount of processed blood per week by increasing frequency and/or duration of the sessions distinctly increases removal. Public Library of Science 2016-01-22 /pmc/articles/PMC4723122/ /pubmed/26799394 http://dx.doi.org/10.1371/journal.pone.0147159 Text en © 2016 Eloot et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Eloot, Sunny
Schneditz, Daniel
Cornelis, Tom
Van Biesen, Wim
Glorieux, Griet
Dhondt, Annemie
Kooman, Jeroen
Vanholder, Raymond
Protein-Bound Uremic Toxin Profiling as a Tool to Optimize Hemodialysis
title Protein-Bound Uremic Toxin Profiling as a Tool to Optimize Hemodialysis
title_full Protein-Bound Uremic Toxin Profiling as a Tool to Optimize Hemodialysis
title_fullStr Protein-Bound Uremic Toxin Profiling as a Tool to Optimize Hemodialysis
title_full_unstemmed Protein-Bound Uremic Toxin Profiling as a Tool to Optimize Hemodialysis
title_short Protein-Bound Uremic Toxin Profiling as a Tool to Optimize Hemodialysis
title_sort protein-bound uremic toxin profiling as a tool to optimize hemodialysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4723122/
https://www.ncbi.nlm.nih.gov/pubmed/26799394
http://dx.doi.org/10.1371/journal.pone.0147159
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