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Contralateral Stimulation, Using TENS, of Phantom Limb Pain: Two Confirmatory Cases

2009· article· en· W2152249017 on OpenAlexaboutno aff
Orazio Giuffrida, Lyn Simpson, Peter W. Halligan

Bibliographic record

VenuePain Medicine · 2009
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAmputationPhantom limbPhysical therapyPhantom limb painVisual analogue scaleRandomized controlled trialPhantom painPhysical medicine and rehabilitationUpper limbSurgery

Abstract

fetched live from OpenAlex

OBJECTIVES: This study aims to evaluate the effectiveness of trans-electric nerve stimulation (TENS) for phantom limb pain applied to contralateral limb (nonamputated limb). DESIGN: Two detailed single case studies using TENS on the contralateral limb are reported in a longitudinal study with one-year follow-up. Five variables were measured across this period. The study comprised of five sequential stages (Pre-assessment, Preliminary baseline, Start of intervention, Extended assessment, One-year follow-up). SETTING AND PATIENTS: Patients were identified at the Rookwood Hospital in Cardiff. They subsequently received regular home visits. The first patient was a 24-year-old male who had suffered a left below-elbow amputation following a car crash. The second patient was a 38-year-old male who had a transfemoral right amputation further to a viral infection. MEASURES: The following semistructured interview and questionnaires were used: McGill Comprehensive pain questionnaire part A and B; The Cambridge Phantom Limb Profile; The Groningen Questionnaire: Problems after Arm Amputation; and 13 Visual Analog Scales. CONCLUSIONS: Both patients showed a significant improvement in their perception of phantom limb pain and sensations that was maintained at one-year follow-up. A randomized blinded controlled trial to confirm these positive outcomes is required.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.341
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.040
GPT teacher head0.334
Teacher spread0.294 · 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 teacher head, 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

Citations51
Published2009
Admission routes1
Has abstractyes

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