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A case of apparent canine erysipeloid associated with<i>Erysipelothrix rhusiopathiae</i>bacteraemia

2012· article· en· W2154537563 on OpenAlexaboutno aff
Jonathan D. Foster, Faye A. Hartmann, Karen A. Moriello

Bibliographic record

VenueVeterinary Dermatology · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsnot available
Fundersnot available
KeywordsErysipelothrix rhusiopathiaeMedicineCellulitisLethargyDermatologyErysipelasAzathioprineAmoxicillinDiseaseInternal medicineMicrobiologyAntibioticsBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Erysipelothrix rhusiopathiae is a Gram-positive facultative anaerobe found worldwide and is most commonly associated with skin disease in swine, while anecdotal reports of cases in dogs have been associated with endocarditis. HYPOTHESIS/OBJECTIVES: Clinicians should consider systemic infectious diseases as a potential cause of erythematous skin lesions. ANIMALS: A 5-year-old female spayed Labrador retriever presented with lethargy, anorexia and erythematous skin lesions while receiving immunosuppressive therapy for immune-mediated haemolytic anaemia. Four days prior to presentation, the dog had chewed on a raw turkey carcase. METHODS: Complete blood count, serum chemistry profile, urinalysis and blood cultures. RESULTS: Blood cultures yielded a pure growth of E. rhusiopathiae serotype 1b. Amoxicillin 22 mg/kg orally twice daily for 2 weeks and discontinuation of azathioprine resulted in remission of fever and skin lesions. CONCLUSIONS AND CLINICAL IMPORTANCE: This report is the first documentation, to the best of the authors' knowledge, of Erysipelothrix infection, a known zoonosis, in an immunosuppressed dog, highlighting the need for infectious disease monitoring in patients receiving such therapy. This information may also help educate veterinarians to include Erysipelothrix infection as a differential diagnosis in dogs with fever and skin lesions, as well as the role of blood cultures in diagnosing this disease.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.280
Teacher spread0.249 · 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 designBench or experimental
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
Published2012
Admission routes1
Has abstractyes

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