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Carpometacarpal Osteoarthritis in Thirty‐Three Horses

2009· article· en· W2123320847 on OpenAlexaff
Luca Panizzi, Spencer Μ. Barber, Hayley M. Lang, James L. Carmalt

Bibliographic record

VenueVeterinary Surgery · 2009
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineLamenessOsteoarthritisRadiographyClinical significanceSurgeryCarpometacarpal jointInternal medicinePathologyAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe signalment, clinical, and radiographic changes associated with carpometacarpal osteoarthritis (CMC-OA) and to report long-term outcome. STUDY DESIGN: Case series. ANIMALS: Horses (n=33) with CMC-OA. METHODS: Medical records (1992-2007) of horses diagnosed with CMC-OA were reviewed and signalment, clinical, and radiographic findings retrieved. Owners were contacted for information on the impact of lameness on intended use, response to treatment, progression of lameness, outcome, and owner satisfaction with response to treatment. RESULTS: CMC-OA identified in 39 limbs, occurred predominantly in middle-aged and older Quarter Horses and Arabians, and caused severe lameness that prevented normal use. Characteristic swelling was centered over the 2nd metacarpal bone/2nd carpal bone articulation. Radiographic changes consisted of proliferative new bone, narrowed joint space, and subchondral lysis. Of 20 horses with follow-up, 7 of 14 treated horses were euthanatized within 4 years and 4 of 5 nontreated horses within 3 years. Response to treatment was short lived and considered very poor by most owners. CONCLUSION: CMC-OA seemingly occurs primarily in Quarter Horses and Arabians in our region. Response to conservative treatment is very poor and short-lived with most horses being euthanatized. CLINICAL RELEVANCE: Conventional treatment methods are unsuccessful for treating 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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.134
GPT teacher head0.366
Teacher spread0.232 · 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; both teacher heads agree on what is shown here.

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

Citations20
Published2009
Admission routes1
Has abstractyes

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