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Record W7117306429 · doi:10.1002/vrc2.70311

Intravascular lymphoma presenting with destructive rhinitis in a dog with epistaxis

2025· article· en· W7117306429 on OpenAlexaboutno aff
Kimberly Si Min Lim, Troy Aaron Bunn, Timothy Siang Yong Foo

Bibliographic record

VenueVeterinary Record Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsLymphomaNasal administrationImmunohistochemistryNoseHistopathologyTranexamic acidNasal cavity

Abstract

fetched live from OpenAlex

Abstract Intravascular lymphoma is a rare form of lymphoma characterised by the proliferation of neoplastic lymphocytes within blood vessels, with a reported predilection for the central nervous system in dogs. An 8.5‐year‐old, female, spayed labrador retriever presented with a 3‐week history of intermittent sneezing and bilateral epistaxis. Computed tomography identified bilateral nasal turbinate lysis and an ill‐defined hyperattenuating left forebrain mass. Rhinoscopy confirmed the intranasal changes, and nasal mucosal biopsies were obtained. Severe epistaxis unresponsive to administration of tranexamic acid was observed post‐rhinoscopy, followed by cardiorespiratory arrest secondary to blood aspiration; resuscitation was declined. Fungal culture of the intranasal biopsies was negative. Histopathological analysis and immunohistochemistry performed on the nasal mucosal biopsies revealed a null‐cell, proliferating large cell lymphoma within the nasal blood vessels, indicative of intravascular lymphoma. This report describes the first case of intravascular lymphoma manifesting with destructive rhinitis in a dog.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
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 head0.027
GPT teacher head0.327
Teacher spread0.300 · 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 designCase report
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
Published2025
Admission routes1
Has abstractyes

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