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Treatment of Carpometacarpal Osteoarthritis by Arthrodesis in 12 Horses

2009· article· en· W1579542216 on OpenAlexaff
Spencer Μ. Barber, Luca Panizzi, Hayley M. Lang

Bibliographic record

VenueVeterinary Surgery · 2009
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineArthrodesisOsteoarthritisLamenessSurgeryAnkylosisRadiographyPhysical therapy

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate arthrodesis as a treatment for carpometacarpal joint osteoarthritis (CMC-OA). STUDY DESIGN: Case series. ANIMALS: Horses (n=12) with CMC-OA. METHODS: Arthrodesis was facilitated by insertion and fanning of a drill bit into the CMC joint at several (3-5) locations in 15 limbs. Follow-up radiographs were obtained for 7 horses (9 limbs). Outcome was determined by telephone survey of owners based on postoperative pain, return to use, appearance of the limb, and success of treatment. RESULTS: Postoperative pain was slight or moderate in 10 of 12 (83%) horses during the first 30 days, and 11 of 12 (92%) horses were markedly improved by 6 months and capable of returning to work. Radiographically 6 CMC joints had a bony ankylosis at follow-up whereas 3 did not (mean 8.7 months). On long-term follow-up (mean 28.6 months) all horses had reduced severity of lameness, 10 of 12 (83%) were considered "sound," 8 (67%) returned to their original activity, and all owners considered arthrodesis highly successful as a treatment. CONCLUSION: A drilling technique that produced CMC arthrodesis, allowed most horses to return to their original activity and was considered successful by all clients. CLINICAL RELEVANCE: Arthrodesis of the CMC joint should be considered a treatment option for CMC-OA.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0020.000
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 head0.121
GPT teacher head0.364
Teacher spread0.243 · 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

Citations18
Published2009
Admission routes1
Has abstractyes

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