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Record W1968574283 · doi:10.3415/vcot-10-01-0016

Osteosarcoma masked by osteomyelitis and cellulitis in a dog

2010· article· en· W1968574283 on OpenAlexaff
Sarah E. Boston, Amar B. Singh, Karen Murphy, Stephanie Nykamp

Bibliographic record

VenueVeterinary and Comparative Orthopaedics and Traumatology · 2010
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMedicineOsteomyelitisCellulitisHumerusLamenessAmputationOsteosarcomaSurgeryRadiographyRadiologyPathology

Abstract

fetched live from OpenAlex

CASE DESCRIPTION: This clinical report describes a 10-year-old female spayed German Shepherd dog cross that was presented with cellulitis of the left proximal forelimb and osteomyelitis of the left proximal humerus, and was ultimately diagnosed with metastatic osteosarcoma. CLINICAL FINDINGS: The diagnosis of cellulitis and osteomyelitis was made using ultrasound, radiography, cytology and histopathology, all of which were consistent with cellulitis and osteomyelitis. Cultures were negative. TREATMENT: The patient was treated using two surgical debridements and long-term broad-spectrum antibiotic drugs. Despite surgical and medical treatment, the dog's condition progressed. A lytic lesion of the left proximal humerus was identified radiographically. OUTCOME: One hundred forty-one days after initial presentation, the dog was presented with a non-weight bearing lameness of the left forelimb. An amputation was scheduled. Preoperative computed tomography scan of the thorax revealed gross metastatic disease to the lungs. The patient was euthanatized and a post-mortem examination revealed osteosarcoma of the left proximal humerus with widespread metastasis. CLINICAL RELEVANCE: To our knowledge, this case is the first reported case of osteomyelitis masking osteosarcoma in a dog. It serves as a reminder to maintain a high index of suspicion when managing cases with a signalment, history and radiographic lesion that are consistent with a primary bone tumour.

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 score0.128
Threshold uncertainty score0.888

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.052
GPT teacher head0.341
Teacher spread0.289 · 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

Citations9
Published2010
Admission routes1
Has abstractyes

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