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Record W3133153767 · doi:10.48336/ztwr-jh26

Assessment of localized pain sensitivity over the transtibial residual limb and its variability among male veterans with amputation

2021· dissertation· en· W3133153767 on OpenAlexaff
Kamiar Ghoseiri

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2021
Typedissertation
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedicineAmputationPhysical therapyProsthesisResidualPhysical medicine and rehabilitationSurgery

Abstract

fetched live from OpenAlex

Localization of pain sensitization has clinical importance, however, rarely been assessed in amputees. The objective of this study was to investigate the sensitivity of pain over the residual limb and its variability among veterans with transtibial amputation. Pain sensitivity in 12 locations was explored twice in 19 veteran amputees using pressure algometry. The lowest pressure pain threshold (PPT) and pressure tolerance (PT) was recorded at the distal end of the residual limb (20.5 and 33 Ncm⁻², p=0.13), and the highest PPT and PT was recorded at the mid-patellar tendon (73.4 and 94.3 Ncm⁻², p=0.03). There was a significant moderate correlation (r=0.48-0.52) between pressure pain and daily hours of prosthesis use. A localized pattern for sensitivity to pain over the transtibial residual limb was obtained that can be used to improve the transtibial socket design and fit as well as the selection of prevention, evaluation, and treatment methods.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.277
Teacher spread0.259 · 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 designObservational
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

Citations0
Published2021
Admission routes1
Has abstractyes

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