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Record W3200764688 · doi:10.33137/cpoj.v4i2.35208

ADJUSTABLE-VOLUME PROSTHETIC SOCKETS: MARKET OVERVIEW AND VALUE PROPOSITIONS

2021· article· en· W3200764688 on OpenAlexvenueno aff
Tyler D. Klenow, J.-U. Schulz

Bibliographic record

VenueCanadian Prosthetics & Orthotics Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsnot available
Fundersnot available
KeywordsVolume (thermodynamics)Modular designComputer scienceReduction (mathematics)Biomedical engineeringEngineeringMathematics

Abstract

fetched live from OpenAlex

The prosthetic socket is commonly considered to be the most important part of the prosthesis and lack of fit can lead to skin breakdown, reduction in wear, reduction in activity, and consequential deleterious health effects. Furthermore, approximately 90% of amputations are due to a vascular etiology, which affect fluid retention regularity, and even small limb volume fluctuations can lead to lack of fit. Adjustability in the socket volume has been suggested as a potential solution to common fit issues but has lacked market penetration mostly due to lack of reimbursement. Despite this there are several adjustable-volume sockets emerging on the market today including prefabricated, modular, custom with adjustable-volume component, custom with adjustable-volume feature, and adjustable-hybrid sockets. Prefabricated sockets are mass produced in common sizes and fit directly to the patient by a prosthetist using pad kits, BOA dials, or straps. Modular sockets are assembled to a patient or model with panels or struts attached to an adjustable base. Custom sockets with adjustable-volume elements are traditionally-fabricated sockets made to a model of a patient's limb with a volume-adjustable component added or volume-adjustable feature built in. Custom-hybrid sockets are made custom to a model of the patient's limb and incorporate several aspects of the previous socket types and include some radically-unique design aspects which cannot be limited to one category. These adjustable-volume sockets offer several advantages to traditional rigid-volume sockets for the patient, prosthetist, and providing clinic. The micro-adjustability for the patient allows them to alter fit without removing the socket, maintaining a more intimate fit throughout the day than traditional sockets. The macro-adjustability for the prosthetist allows for increased options for fit customization including the ability to reverse or undo changes without necessarily re-making the socket. This allows for the most optimal fit for the patient. Adjustable volume also present efficiencies in the fitting process by simplifying or eliminating steps including residual limb shape capture, form modification, diagnostic fabrication, iterative alteration, and definitive fabrication with the different socket types affecting different steps. Due to these factors, adjustable-volume sockets have disrupted the market to the point where reimbursement reform is needed including additional L-codes in the United States and fee-for-service or fee-for-outcome associated with prosthetic follow-up care. Prosthetic care should also be separated from durable medical equipment to allow for alternative reimbursement models. As reimbursement adapts prosthetists must adapt correspondingly to differentiate their skillset from other allied health providers including incorporating more objective methods to show superior care outcomes. This adaptation should include a continued push for state and municipal licensure of prosthetists.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.999
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0070.007
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0190.006

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 head0.203
Teacher spread0.195 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations40
Published2021
Admission routes1
Has abstractyes

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