Clinicopathologic features of an unusual outbreak of cryptococcosis in dogs, cats, ferrets, and a bird: 38 cases (January to July 2003)
Bibliographic record
Abstract
OBJECTIVE: To determine clinical and pathologic findings associated with an outbreak of cryptococcosis in an unusual geographic location (British Columbia, Canada). DESIGN: Retrospective study. ANIMALS: 1 pink-fronted cockatoo, 2 ferrets, 20 cats, and 15 dogs. PROCEDURE: A presumptive diagnosis of cryptococcosis was made on the basis of serologic, histopathologic, or cytologic findings, and a definitive diagnosis was made on the basis of culture or immunohistochemical staining. RESULTS: No breed or sex predilections were detected in affected dogs or cats. Eleven cats had neurologic signs, 7 had skin lesions, and 5 had respiratory tract signs. None of 17 cats tested serologically for FeLV yielded positive results; 1 of 17 cats yielded positive results for FIV (western blot). Nine of 15 dogs had neurologic signs, 2 had periorbital swellings, and only 3 had respiratory tract signs initially. Microbiologic culture in 15 cases yielded 2 isolates of Cryptococcus neoformans var grubii (serotype A) and 13 isolates of C. neoformans var gattii (serotype B); all organisms were susceptible to amphotericin B and ketoconazole. Serologic testing had sensitivity of 92% and specificity of 98%. CONCLUSIONS AND CLINICAL RELEVANCE: Serologic titers were beneficial in identifying infection in animals with nonspecific signs, but routine serum biochemical or hematologic parameters were of little value in diagnosis. Most animals had nonspecific CNS signs and represented a diagnostic challenge. Animals that travel to or live in this region and have nonspecific malaise or unusual neurologic signs should be evaluated for cryptococcosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".