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Record W2511096238 · doi:10.1177/0309364616661255

Differences in orthotic design for thumb osteoarthritis and its impact on functional outcomes

2016· article· en· W2511096238 on OpenAlexaff
Pedro Henrique Almeida, Joy C. MacDermid, Tatiana Barcelos Pontes, Clarissa Cardoso dos Santos Couto Paz, João Paulo Chieregato Matheus

Bibliographic record

VenueProsthetics and Orthotics International · 2016
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsMcMaster University
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsThumbOsteoarthritisFoot OrthosesMedicinePhysical therapyPhysical medicine and rehabilitationEvidence-based medicinePsychological interventionAlternative medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Orthoses are a well-known intervention for the treatment of thumb osteoarthritis; however, there is a multitude of orthotic designs and not enough evidence to support the efficacy of specific models. OBJECTIVE: To examine the influence of different orthoses on pain, hand strength, and hand function of patients with thumb osteoarthritis. STUDY DESIGN: Literature review. METHODS: A scoping literature review of 14 publications reporting orthotic interventions for patients with thumb osteoarthritis was conducted. Functional outcomes and measures were extracted and analyzed. RESULTS: In total, 12 studies reported improvements in pain and hand strength after the use of thumb orthoses. Comparisons between different orthotic designs were inconclusive. CONCLUSION: The use of orthoses can decrease pain and improve hand function of patients with thumb osteoarthritis; however, the effectiveness of different orthoses still needs support through adequate evidence. Clinical relevance Multiple orthoses for thumb osteoarthritis are available. Although current studies support their use to improve pain and hand function, there is no evidence to support the efficacy of specific orthotic designs. Improved functional outcomes can be achieved through the use of short orthoses, providing thumb stabilization without immobilizing adjacent joints.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.037
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.037
GPT teacher head0.302
Teacher spread0.265 · 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

Citations11
Published2016
Admission routes1
Has abstractyes

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