ReviewMembranes2022
Interaction of Human Serum Albumin with Uremic Toxins: The Need of New Strategies Aiming at Uremic Toxins Removal.
Review in Membranes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- Kidney clearances of protein-bound uremic toxins predict outcomes in chronic kidney disease: a prospective cohort study.Renal failure · 2025Article
- A scoping review on the possible immunometabolic properties of the furan fatty acid metabolite 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid.The American journal of clinical nutrition · 2025Article
- Portimine A maintains bioactivity following exposure to liver microsomes and cell lysates: no evidence for significant metabolic inactivation.Medical oncology (Northwood, London, England) · 2025Article
- UnravelingFrontiers in pharmacology · 2025Review
- Binding and detoxification efficiency of albumin decline after haemodialysis.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024Article
- Article
- A Novel Strategy for Enhanced Sequestration of Protein-Bound Uremic Toxins Using Smart Hybrid Membranes.Journal of functional biomaterials · 2023Article
- Adsorption- and Displacement-Based Approaches for the Removal of Protein-Bound Uremic Toxins.Toxins · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chronic kidney disease (CKD) is acknowledged worldwide to be a grave threat to public health, with the number of US end-stage kidney disease (ESKD) patients increasing steeply from 10,000 in 1973 to 703,243 in 2015. Protein-bound uremic toxins (PBUTs) are excreted by renal tubular secretion in healthy humans, but hardly removed by traditional haemodialysis (HD) in ESKD patients. The accumulation of these toxins is a major contributor to these sufferers' morbidity and mortality. As a result, some improvements to dialytic removal have been proposed, each with their own upsides and drawbacks. Longer dialysis sessions and hemodiafiltration, though, have not performed especially well, while larger dialyzers, coupled with a higher dialysate flow, proved to have some efficiency in indoxyl sulfate (IS) clearance, but with reduced impact on patients' quality of life. More efficient in removing PBUTs was fractionated plasma separation and adsorption, but the risk of occlusive thrombosis was worryingly high. A promising technique for the removal of PBUTs is binding competition, which holds great hopes for future HD. This short review starts by presenting the PBUTs chemistry with emphasis on the chemical interactions with the transport protein, human serum albumin (HSA). Recent membrane-based strategies targeting PBUTs removal are also presented, and their efficiency is discussed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.