Prognostic Factors in Cats with Feline Panleukopenia
Bibliographic record
Abstract
BACKGROUND: Feline panleukopenia is a highly contagious and often lethal disease. OBJECTIVE: The purpose of the study was to identify prognostic factors for survival of cats with panleukopenia. ANIMALS: Between 1990 and 2007, 244 cats were diagnosed with panleukopenia in the Clinic of Small Animal Medicine, LMU University of Munich, Germany. Diagnosis was established by electron microscopy, polymerase chain reaction of feces or blood, antigen ELISA of feces, pathognomonic histopathological lesions at necropsy, or some combination of these procedures. METHODS: Medical records of each cat were evaluated retrospectively. RESULTS: Survival rate was 51.1%. No significant correlation was found between outcome and living conditions, age, vaccination status (unvaccinated versus one or more vaccines administered), or severity of clinical signs. However, of the vaccinated cats, none had received a vaccine later than 12 weeks of age as a kitten. Nonsurvivors had significantly lower leukocyte and thrombocyte counts at presentation compared with survivors. The relative risk of death for patients with <1,000/μL leukocytes was 1.77 times as high as in patients with a leukocyte count of 1,000-2,500/μL (P=.038), and 1.85 times as high as in patients with >2,500/μL leukocytes (P=.001). The likelihood of a fatal outcome was higher when serum albumin concentration was <30 g/L or serum potassium concentration <4 mmol/L. CONCLUSIONS AND CLINICAL IMPORTANCE: Vaccination strategies that do not include vaccination of kittens beyond 12 weeks of age may not be adequate to prevent panleukopenia. Leukopenia, thrombocytopenia, hypoalbuminemia, and hypokalemia are negative prognostic factors in cats with panleukopenia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".