Evidence map›Paper›PMID 34784606›Full record

ArticleNephron2022

Soft Target Weight: Theory and Simulation of a Novel Haemodialysis Protocol Which Reduces Excessive Ultrafiltration.

Damien Ashby, Richard Corbett, Neill Duncan

Abstract read
In one paragraph

Article in Nephron, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Bioimpedance-derived euvolemic weight varies in hemodialysis patients-challenging the fixed target weight concept.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024
    Article
  3. Review
  4. Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Damien AshbyWest London Renal and Transplant Centre, Imperial College Healthcare NHS Trust, Hammersmith Hospital, London, United Kingdom.
Richard CorbettWest London Renal and Transplant Centre, Imperial College Healthcare NHS Trust, Hammersmith Hospital, London, United Kingdom.
Neill DuncanWest London Renal and Transplant Centre, Imperial College Healthcare NHS Trust, Hammersmith Hospital, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionExcessive ultrafiltration is associated with intra-dialytic symptoms, loss of residual function, and mortality in haemodialysis patients. A major contributor to excessive ultrafiltration is within-individual variation in pre-dialysis weight and the concept of achieving a fixed target weight by the end of each dialysis session. Haemodialysis protocols which allow variable post-dialysis weight have not been proposed.

methodsWeight variation was observed in haemodialysis patients and healthy controls to estimate the proportion of pre-dialysis weight variation which could be considered natural variation. These estimates were used to derive a novel protocol for setting ultrafiltration, which was evaluated by mathematical modelling.

resultsAmongst 20 haemodialysis patients, mean (SD) pre-dialysis weight was 102.74 (0.94)% of target weight after a 2-day gap and 103.50 (0.94)% after a 3-day gap. Amongst 10 healthy individuals, mean (SD) daily weight was 100.0 (0.71)% of average weight. A 4-component model of pre-dialysis weight was derived using these estimates, in which the best estimate of pre-dialysis excess fluid is the midpoint of excess weight and average fluid gain, and used to propose a novel protocol for ultrafiltration setting. In simulations, the novel protocol reduced ultrafiltration variation by more than half (standard deviation 0.6 vs. 1.3% of target weight, p < 0.001), without increasing the variation in post-dialysis fluid excess. Excessive ultrafiltration rates (over 13 mL/h/kg) were far less frequent using this protocol (2.6% vs. 7.5% of sessions, p = 0.001).

conclusionConsidering natural weight variation allows the development of a novel protocol for ultrafiltration in which target weight does not have to be achieved precisely: it is therefore a soft target. This protocol, which is predicted to substantially reduce excessive ultrafiltration variation, is a zero-cost intervention with the potential to improve symptoms and clinical outcome for haemodialysis patients.

Indexed as

Renal DialysisUltrafiltrationComputer SimulationHumansModels, TheoreticalWeight GainDialytic symptomsDry weightHaemodialysisIntra-dialytic hypotensionUltrafiltration

Identifiers

PMID34784606
PMCPMC8985015

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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.