Clinicopathological findings of FeLV- positive cats at a secondary referral center in Florida, USA (2008–2019)
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to describe the seroprevalence, presenting complaint, clinicopathological changes, co-morbidities and outcomes of feline leukemia virus positive cats presented to a specialty referral center in Florida, USA. METHODS: In this retrospective study, medical records of 8050 cats presented to a private referral center from August 2008 to September 2019 were reviewed. Inclusion criteria required was a positive result for feline leukemia virus by point-of-care antigen testing or immunofluorescence assay. RESULTS: Forty-one cases met the inclusion criteria. Of 2002 cats that were tested, 41 cats (2%) met the inclusion criteria. One cat had a negative point of care antigen test result and positive bone marrow IFA result. The mean age at diagnosis was 9 years. The main reasons for presentation were abnormal complete blood cell count results (35%), followed by pleural effusion (18%), and anorexia (15%). The most common laboratory abnormalities included anaemia (71%), of which 74% had a nonregenerative anemia, thrombocytopenia (52%), elevated aspartate aminotransferase (50%), hyperbilirubinemia (35%), and hypokalemia (35%). Seven percent of cats (3/41) were also positive for feline immunodeficiency virus. The most common diagnoses were neoplasia (76%) and bone marrow disorders (12%). Cats with neoplasia were significantly younger. Survival to discharge was 88%. CONCLUSION AND RELEVANCE: Results of this study show that feline leukemia virus is uncommon in secondary referral center, even if this represents a population of unhealthy cats. The most common associated diagnosis was neoplasia, which was more likely to be seen in younger cats (< 4 years of age). The mean age of cats positive for feline leukemia virus was also older than previously published data. These findings support the current guidelines which indicate that cats presented with clinical illness should be tested for FeLV at the time of presentation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".