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Record W101740420

Metatarsalgia and rheumatoid arthritis--a randomized, single blind, sequential trial comparing 2 types of foot orthoses and supportive shoes.

2000· article· en· W101740420 on OpenAlexaff
Andrew Chalmers, Chris Busby, Jill Goyert, B. B. Porter, Michael Schulzer

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsVancouver Hospital and Health Sciences Centre
Fundersnot available
KeywordsMedicineMetatarsalgiaRheumatoid arthritisPhysical therapyCrossover studySynovitisRandomized controlled trialPsychological interventionFoot (prosody)Foot OrthosesSurgeryForefootInternal medicineComplicationPlacebo
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare the effects of semi-rigid and soft orthoses worn in supportive shoes, and supportive shoes worn alone, on metatarsal phalangeal (MTP) joint pain. MTP joint synovitis, and lower extremity function in patients with rheumatoid arthritis. METHODS: Twenty-eight subjects referred to occupational therapy received in random order 3 interventions for 12 week trials, separated by 2 week washouts. A crossover design compared effectiveness of interventions. RESULTS: Twenty-four subjects completed the study. A reduction in mean pain scores from baseline to final visits showed that semi-rigid orthoses had a highly significant effect on pain. Soft orthoses did not show a significant effect on pain from baseline to final visit, nor did shoes worn alone. None of the interventions had a significant effect on synovitis or function. CONCLUSION: Semi-rigid orthoses worn in supportive shoes were an effective treatment for metatarsalgia. Supportive shoes worn alone or worn with soft orthoses did not provide pain relief for metatarsalgia.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.040
GPT teacher head0.248
Teacher spread0.207 · 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 designRandomized trial
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

Citations124
Published2000
Admission routes1
Has abstractyes

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