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Record W2965173619 · doi:10.33137/cpoj.v2i1.32723

The influence of perforated prosthetic liners on residual limb wound healing: a case report

2019· article· en· W2965173619 on OpenAlexvenueaboutno aff
Michael McGrath, Joseph McCarthy, Ana Gallego, Alan Kercher, Saeed Zahedi, David Moser

Bibliographic record

VenueCanadian Prosthetics & Orthotics Journal · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlanarian Biology and Electrostimulation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAmputationCushioningSoft tissueSurgeryMaterials science

Abstract

fetched live from OpenAlex

CASE DESCRIPTION: Good residual limb skin health is vital to successful prosthetic prescription. Unnatural loading profiles and excessive sweating can lead to skin and soft tissue problems. Perforated liners allow the transport of moisture away from the skin and allow negative pressure (a condition that has been shown to aid wound healing) to act directly on the residuum surface. AIM: Assess the effects of perforated prosthetic liner use, particularly with respect to wound healing. METHOD: Three patient histories were retrospectively reviewed following prescription of perforated prosthetic liners due to excessive sweating or prolonged residual limb health concerns. Photographic records from patient files were used to document changes in residual limb condition. Patients also provided subjective feedback regarding their experiences. FINDINGS: Two cases described active amputees with persistent blistering irritated during exercise. Another case described a patient of low mobility level with a history of residual limb skin infections. All saw their conditions heal and reported a reduction in problematic sweating. Two patients reported cancelling surgical interventions after substantial improvements with the perforated liner. DISCUSSION: These findings provide evidence that the use of perforated prosthetic liners allow improvements in residual limb health, while still permitting prosthetic use. LAYMAN’S ABSTRACT For lower limb amputees, excessive sweating is a common issue affecting their quality of life. It is particularly problematic for the skin of the amputated limb, which may be scarred and is loaded unnaturally by the prosthetic socket. Silicone liners are often worn to provide a close fit and for cushioning but they create a warm environment that traps sweat against the skin, leading to bacterial growth. Additionally, sweat on the skin can increase the amount of movement between the amputated limb and the socket, affecting prosthetic control. In order to address this problem, silicone liners have been designed with perforations in them to allow warm air and sweat to move away from the skin. This report describes three cases of patients who suffered from long-standing wounds, blisters or skin infections on their amputated limbs. Each was prescribed with a perforated silicone liner and changes in their skin conditions were observed. In all cases, the wounds healed and each patient reported a noticeable reduction in problematic sweating on their residual limb, without limiting their prosthetic use. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32723/25281 How to Cite: McGrath M, McCarthy J, Gallego A, Kercher A, Zahedi S, Moser D. The influence of perforated prosthetic liners on residual limb wound healing: a case report. Canadian Prosthetics & Orthotics Journal. 2019; volume2, Issue1, No.3. https://doi.org/10.33137/cpoj.v2i1.32723 CORRESPONDING AUTHOR:Dr. Michael McGrath, Research Scientist–Clinical Evidence Blatchford Group, Unit D Antura, Bond Close, Basingstoke, RG24 8PZ, United Kingdom Email: mike.mcgrath@blatchford.co.uk

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.237
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2019
Admission routes2
Has abstractyes

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