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Record W4205477383 · doi:10.3410/f.735710185.793562543

Faculty Opinions recommendation of A comparison of the effects of mirror therapy and phantom exercises on phantom limb pain

2019· dataset· en· W4205477383 on OpenAlexaff
Joel Katz

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2019
Typedataset
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsYork University
Fundersnot available
KeywordsBeck Depression InventoryVisual analogue scalePhantom limbMedicinePhantom limb painPhysical therapyPhantom painQuality of life (healthcare)Imaging phantomIntensity (physics)Significant differencePhysical medicine and rehabilitationAmputationSurgeryInternal medicineNuclear medicineAnxietyNursing

Abstract

fetched live from OpenAlex

Background/aim: Although mirror therapy (MT) and phantom exercises (PE) have been shown to reduce pain, the efficacy of these methods in terms of pain, quality of life (QoL), and psychological status (PS) has not been investigated and compared to date. The aim of this study was to determine whether there is any difference between MT and PE in the treatment of phantom limb pain (PLP).Materials and methods: Forty unilateral transtibial amputees (aged 18–45 years) participated in this study. The subjects were randomly divided into ‘MT group’ and ‘PE group’. QoL was assessed using Short-Form 36 (SF-36), psychological status using the Beck depression inventory (BDI), and pain intensity using a visual analog scale (VAS), before and at the end of the program, and on the 3rd and 6th months thereafter.Results: All assessments for all parameters improved significantly in both groups (P < 0.05). Comparison of the two groups revealed a significant difference in changes for VAS and BDI in all measurements, and in pre- and posttreatment scores for all SF-36 parameters (except for Role-Emotional) in favor of the MT group (P < 0.05).Conclusion: While pain intensity decreased and QoL and PS improved in both the MT and PE groups, these improvements were greater in the MT group. PMID: 30762318

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)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.490
Threshold uncertainty score0.728

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.4900.184

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 head0.052
GPT teacher head0.387
Teacher spread0.334 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2019
Admission routes1
Has abstractyes

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