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P‐66 
Disseminated histiocytic sarcoma in a dog receiving long‐term immunosuppressive therapy

2004· article· en· W2027544775 on OpenAlexaboutno aff
Akiko Kawabata, Miyo Aoki-Ota, Mitsuhiro Sekiguchi, Yasuyuki Momoi, T. Iwaski

Bibliographic record

VenueVeterinary Dermatology · 2004
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHistiocytic sarcomaPrednisoloneDermatologySarcomaNodule (geology)SurgeryHistiocytePathology

Abstract

fetched live from OpenAlex

A 4‐year‐old female Labrador retriever that had been receiving prednisolone for over 8 months because of severe pruritus developed iatrogenic Cushing's syndrome and was referred to our hospital. After complete withdrawal of prednisolone, atopic dermatitis was diagnosed, based on clinical signs, history, an elimination diet test and an intradermal test. Immunotherapy was started, but it was discontinued 3 months later due to lack of improvement. Several drugs, including prednisolone and cyclosporine, were used in an attempt to control the pruritus, and amitriptyline was added for psychogenic treatment. When the dog was 5.5 years old, dome‐shaped and nonpainful nodules were detected on the digits, neck and shoulder. Three months after the first nodule was detected, nodules had developed all over the body, and most were ulcerated. The nodules were examined histopathologically and the diagnosis was disseminated histiocytic sarcoma. As disseminated histiocytic sarcoma has a reportedly poor prognosis, only antibiotic therapy in addition to continuous amitriptyline and prednisolone administration was pursued. The dog died 6 months after the first nodule was detected. The dog received immunosuppressive agents long‐term to control severe pruritus due to atopic dermatitis. There is a possibility that a long‐term immunocompromised state may lead to the development of neoplasms, such as disseminated histiocytic sarcoma. Funding: Self‐funded.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.044
GPT teacher head0.370
Teacher spread0.326 · 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.

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

Citations0
Published2004
Admission routes1
Has abstractyes

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