For designing and evaluating the dialyzer and investigating the optimal therapeutic conditions, in vitro studies bring us many useful findings. In hemodialysis, however, the membrane fouling due to protein molecules reduces solute removal performance. Therefore, we investigated a method for replicating the fouling in dialyzers in aqueous experiments. After the albumin solution was circulated in the test circuit with a dialyzer, a glutaraldehyde solution was pumped into the dialyzer to immobilize albumin on the hollow fiber membrane. Under various immobilization conditions, the permeability of creatinine and vitamin B12 was evaluated by dialysis experiments.
The creatinine clearance after immobilization of albumin was decreased, suggesting pore plugging by our fouling replication method. The glutaraldehyde crosslinked albumin molecules that adhered them to the membrane firmly. Moreover, the degree of fouling may be controlled by changing the concentration of albumin solution and the volume of glutaraldehyde solution used for immobilization. Our fouling replication method was applied to three types of polyester polymer alloy (PEPA) dialyzers and one polysulfone (PSf) dialyzer. This method enables to evaluate the permeability of various dialyzers with fouling in vitro that will be of great help in collecting data for designing dialyzers.
Comparative efficacy between hemodialysis using super high-flux dialyzer with hemoperfusion and high-volume postdilution online hemodiafiltration in removing protein bound and middle molecule uremic toxins: A cross-over randomized controlled trial
Background: Hemodialysis (HD) using super high-flux dialyzer (HD + SHF) comparably removed uremic toxins to high-volume postdilution online hemodiafiltration (olHDF). Integration of hemoperfusion (HP) to HD + SHF (HD + SHF + HP) might provide superior uremic toxin removing capability to high-volume postdilution olHDF.
Method: The present study was conducted in thrice-a-week HD patients to compare the efficacy in removing indoxyl sulfate (IS), beta-2 microglobulin (β2 M), and urea between high-volume postdilution ol-HDF and HD + SHF + HP, comprising HD + SHF as the main treatment plus HD + SHF + HP 1/week in the first 4 weeks and 1/2 weeks in the second 4 weeks.
Results: Ten prevalent HD patients with blood flow rate (BFR) above 400 ml/min were randomized into two sequences of 8-week treatment periods of HD + SHF + HP and later high-volume postdilution olHDF or vice versa. When compared with high-volume postdilution olHDF (convective volume of 26.02 ± 1.8 L/session), HD + SHF + HP provided comparable values of percentage reduction ratio of IS (52.0 ± 11.7 vs. 56.3 ± 7.5%, p = 0.14) and β2 M (83.7 ± 4.9 vs. 84.0 ± 4.3%, p = 0.37) and slightly lower urea reduction ratio. Despite greater dialysate albumin loss (p = 0.008), there was no significant change in serum albumin level in HD + SHF + HP group.
Conclusions: HD + SHF + HP could not provide superior efficacy in removing uremic toxins to high-volume postdilution olHDF. The use of low BFR of 200 ml/min during the first 2 h of HD + SHF + HP session, according to the instruction of manufacturer, might impair the efficacy of the HD + SHF part in removing uremic toxins.
Design and Development of a Computational Tool for a Dialyzer by Using Computational Fluid Dynamic (CFD) Model
- In order to reduce the hemodialysis cost and duration, an investigation of the effect of dialyzer design and process variables on the solute clearance rate is required. It is not easy to translate the in vivo transfer process with in vitro experiments, as it involves a high cost to produce various designs and membranes for the dialyzer. The primary objective of this study was the design and development of a computational tool for a dialyzer by using a computational fluid dynamic (CFD) model. Due to their complexity, only researchers with expertise in computational analysis can use dialyzer models.
- Therefore, COMSOL Inc. (Stockholm, Sweden) has made an application on membrane dialysis to study the impact of different design and process parameters on dialyzed liquid concentration. Still, membrane mathematical modeling is not considered in this application. This void hinders an investigation of the impact of membrane characteristics on the solute clearance rate.
- This study has developed a stand-alone computational tool in COMSOL Multiphysics 5.4 to fill this void. A review of the literature conducted shows that there are no suitable stand-alone computational tools for kidney dialysis. Very little work has been undertaken to validate the stand-alone computational tool. Medical staff in the hospitals require a computational tool that can be installed quickly and provide results with limited knowledge of dialysis.
- This work aims to construct a user-friendly computational tool to solve this problem. The development of a user-friendly stand-alone computational tool for the dialyzer is described thoroughly. This application simulates a mathematical model with the Finite Element Method using the COMSOL Multiphysics solver. The software tool is converted to a stand-alone version with the COMSOL compiler. The stand-alone computational tool provides the clearance rate of six different toxins and module packing density. Compared with the previous application, the stand-alone computational tool of membrane dialysis enables the user to investigate the impact of membrane characteristics and process parameters on the clearance rate of different solutes.
- The results are also inconsistent with the literature data, and the differences ranges are 0.09-6.35% and 0.22-2.63% for urea clearance rate and glucose clearance rate, respectively. Statistical analysis of the results is presented as mean with 95% confidence intervals (CIs) and p values 0.9472 and 0.833 of the urea and glucose clearance rates, respectively.
Impact of Expanded Hemodialysis Using Medium Cut-off Dialyzer on Quality of Life: Application of Dynamic Patient-Reported Outcome Measurement Tool
Rationale & objective: Current hemodialysis (HD) treatments have limited ability to clear larger-molecular-weight uremic toxins. Retention is associated with increased symptom burden, low health-related quality of life (HRQoL), and high mortality. Improved clearance, using novel medium cut-off dialyzers, termed expanded HD (HDx), may be associated with improved subjective experience. We have previously developed a dynamic patient-reported outcome measure (PROM) instrument to allow iterative recording to better appreciate the overall burden of disease and assess the impact of therapy changes.
Study design: Single-center interventional pilot study.
Setting & participants: 28 patients established on maintenance HD, London, Ontario, Canada.
Intervention: Initial study consisting of 2-week observation (baseline-conventional high-flux HD) followed by 12 weeks of HDx. HRQoL was assessed using the dynamic PROM instrument thrice weekly (enabled in a dedicated app as the London Evaluation of Illness [LEVIL]). Extension phase; 2-week baseline with 24 weeks of HDx and 8-week washout.
Outcomes: Principal aim was to establish whether HDx therapy was associated with improved HRQoL, evidence of dose-dependant response, and whether effects were durable over time, using LEVIL.
Results: Patients with lower LEVIL scores (<70/100) at baseline showed improvement in overall HRQoL after 8 weeks of therapy with similar carryover effect. General well-being, energy, and sleep quality were improved significantly as a consequence of HDx therapy. There were no detrimental effects of HDx detected in patients with higher baseline HRQoL.
Limitations: Small nonrandomized sample size. The coronavirus disease 2019 pandemic interfered with the extension phase.
Conclusions: Dynamic PROM assessment effectively identified patients with lower HRQoL and higher symptom burden, demonstrating durable time/dose-dependent improvements across a range of symptom domains. The use of this instrument may allow targeted selection of patients most likely to benefit from HDx therapy and assist in monitoring response and defining effect size and treatment duration to allow optimal design of further definitive randomized controlled trials of this newly introduced technology.
DiaEasy? Dialyzer (800 µl) MWCO 1 kDa |
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| K1017-25 | Biovision | each | 579.6 EUR |
DiaEasy? Dialyzer (800 µl) MWCO 3.5 kDa |
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| K1018-25 | Biovision | each | 288 EUR |
DiaEasy? Dialyzer (250 µl) MWCO 25 kDa |
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| K1022-10 | Biovision | each | 235.2 EUR |
DiaEasy? Dialyzer (250 µl) MWCO 25 kDa |
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| K1022-25 | Biovision | each | 418.8 EUR |
DiaEasy? Dialyzer (250 µl) Floating racks |
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| 1020-10 | Biovision | each | 124.8 EUR |
DiaEasy? Dialyzer (250 µl) Floating racks |
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| 1020-5 | Biovision | each | 105.6 EUR |
DiaEasy? Dialyzer (800 µl) Floating racks |
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| 1018-10 | Biovision | each | 124.8 EUR |
DiaEasy? Dialyzer (800 µl) Floating racks |
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| 1018-5 | Biovision | each | 105.6 EUR |
DiaEasy? Dialyzer (250 µl) Supporting trays |
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| 1028-10 | Biovision | each | 124.8 EUR |
DiaEasy? Dialyzer (250 µl) Supporting trays |
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| 1028-5 | Biovision | each | 105.6 EUR |
DiaEasy? Dialyzer (800 µl) Supporting trays |
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| 1019-10 | Biovision | each | 124.8 EUR |
DiaEasy? Dialyzer (800 µl) Supporting trays |
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| 1019-5 | Biovision | each | 105.6 EUR |
DiaEasy? Dialyzer (800 µl) MWCO 6-8 kDa |
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| K1019-10 | Biovision | each | 164.4 EUR |
DiaEasy? Dialyzer (800 µl) MWCO 6-8 kDa |
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| K1019-25 | Biovision | each | 288 EUR |
DiaEasy? Dialyzer (250 µl) MWCO 6-8 kDa |
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| K1020-10 | Biovision | each | 138 EUR |
DiaEasy? Dialyzer (250 µl) MWCO 6-8 kDa |
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| K1020-100 | Biovision | each | 574.8 EUR |
DiaEasy? Dialyzer (250 µl) MWCO 6-8 kDa |
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| K1020-25 | Biovision | each | 235.2 EUR |
DiaEasy? Dialyzer (250 µl) MWCO 12-14 kDa |
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| K1021-10 | Biovision | each | 138 EUR |
DiaEasy? Dialyzer (250 µl) MWCO 12-14 kDa |
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| K1021-25 | Biovision | each | 235.2 EUR |
DiaEasy? Dialyzer (20 ml) MWCO 3.5 kDa |
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| K1000-10 | Biovision | each | 216 EUR |
DiaEasy? Dialyzer (20 ml) MWCO 3.5 kDa |
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| K1000-100 | Biovision | each | 1227.6 EUR |
DiaEasy? Dialyzer (20 ml) MWCO 3.5 kDa |
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| K1000-25 | Biovision | each | 411.6 EUR |
DiaEasy? Dialyzer (15 ml) MWCO 3.5 kDa |
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| K1001-100 | Biovision | each | 1227.6 EUR |
DiaEasy? Dialyzer (15 ml) MWCO 3.5 kDa |
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| K1001-25 | Biovision | each | 411.6 EUR |
DiaEasy? Dialyzer (10 ml) MWCO 3.5 kDa |
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| K1002-100 | Biovision | each | 1227.6 EUR |
DiaEasy? Dialyzer (10 ml) MWCO 3.5 kDa |
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| K1002-25 | Biovision | each | 411.6 EUR |
DiaEasy? Dialyzer (20 ml) MWCO 1 kDa |
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| K1009-25 | Biovision | each | 914.4 EUR |
DiaEasy? Dialyzer (15 ml) MWCO 1 kDa |
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| K1010-25 | Biovision | each | 914.4 EUR |
Determinants of Hemodialysis Performance: Modeling Fluid and Solute Transport in Hollow-Fiber Dialyzers
Hemodialysis constitutes the lifeline of patients with end stage renal disease, yet the parameters that affect hemodialyzer performance remain incompletely understood. We developed a computational model of mass transfer and solute transport in a hollow-fiber dialyzer to gain greater insight into the determinant factors. The model predicts fluid velocity, pressure, and solute concentration profiles for given geometric characteristics, membrane transport properties, and inlet conditions. We examined the impact of transport and structural parameters on uremic solute clearance by varying parameter values within the constraints of standard clinical practice.
The model was validated by comparison with published experimental data. Our results suggest solute clearance can be significantly altered by changes in blood and dialysate flow rates, fiber radius and length, and net ultrafiltration rate. Our model further suggests that the main determinant of the clearance of unreactive solutes is their diffusive permeability. The clearance of protein-bound toxins is also strongly determined by blood hematocrit and plasma protein concentrations. Results from this model may serve to optimize hemodialyzer operating conditions in clinical practice to achieve better clearance of pathogenic uremic solutes.