Cryptococcosis in domestic and wild animals: A review
Bibliographic record
Abstract
Cryptococcosis is a fungal disease of public health relevance that affects numerous animal species and humans, causing respiratory and neurological impairment. Hence, we conducted a systematic review that included publications from 1975 to 2021 and covered 132 articles that addressed reports of cryptococcosis in domestic and wild animals, its main clinical manifestations, pathological findings, etiology, diagnosis, and therapeutic protocols. We found that the highest number of reports of cryptococcosis is in domestic species, especially cats. Among the wild and/or exotic animals, koalas and ferrets are the most affected, being important carriers of Cryptococcus spp. Pulmonary and neurological involvement is predominant in all species, although nonspecific clinical manifestations have been reported in various species, making clinical suspicion and diagnosis difficult. The countries with the most reports are Australia, the United States, Brazil, and Canada, with C. gattii VGI and VGII standing out. The therapies were based on azoles, amphotericin B, and 5-flucytosine, although there is no standard treatment protocol. Although, several diagnostic methods have been described, in a significant number of reports the diagnosis was made after a necropsy. Professionals are warned about diverse and nonspecific clinical manifestations in different animal species, which underlines the importance of cryptococcosis in the differential diagnosis in clinical practice. Furthermore, it is necessary to encourage the use of laboratory and molecular tools to improve the diagnosis of cryptococcosis. We also emphasize the urgent need for standardized therapeutic protocols to guide veterinary clinicians.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".