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Record W2108553591 · doi:10.2460/javma.244.3.346

Compartment syndrome associated with expansile antebrachial tumors in two dogs

2014· article· en· W2108553591 on OpenAlexaboutno aff
Lynn C. Maki, Stanley E. Kim, Matthew D. Winter, Kelvin Kow, Julia A. Conway, Daniel D. Lewis

Bibliographic record

VenueJournal of the American Veterinary Medical Association · 2014
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLamenessForelimbPathologicalLabrador RetrieverHumerusAmputationSurgeryPathologyAnatomy

Abstract

fetched live from OpenAlex

CASE DESCRIPTION: A 10-year-old spayed female Jack Russell Terrier and a 7-year-old neutered male mixed-breed dog were evaluated because of acute, progressive, unilateral forelimb lameness associated with signs of pain and turgid antebrachial swelling. CLINICAL FINDINGS: For either dog, there were no salient pathological or diagnostic imaging abnormalities. A diagnosis of compartment syndrome was confirmed on the basis of high caudal antebrachial compartmental pressure in the affected forelimb. TREATMENT AND OUTCOME: Both dogs underwent surgical exploration of the affected forelimb. In each case, an intramuscular tumor (mast cell tumor in the Jack Russell Terrier and suspected sarcoma in the mixed-breed dog) was detected and presumed to be the cause of the high compartmental pressure. At 6 months following tumor excision, the dog with the mast cell tumor did not have any clinical signs of disease. The dog with a suspected sarcoma underwent tumor excision and forelimb amputation at the proximal portion of the humerus followed by chemotherapy; the dog was euthanized approximately 1 year following treatment because of pulmonary metastasis. CLINICAL RELEVANCE: Compartment syndrome is a serious but rarely reported condition in dogs and is typically ascribed to intracompartmental hemorrhage. These 2 cases illustrate the potential for expansile intramuscular antebrachial tumors to cause compartment syndrome in dogs.

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)0.004
metaresearch head score (Gemma)0.003
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 score0.017
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.357
Teacher spread0.330 · 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

Citations7
Published2014
Admission routes1
Has abstractyes

Explore more

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