Coombs’, haemoplasma and retrovirus testing in feline anaemia
Bibliographic record
Abstract
OBJECTIVE: To investigate the associations between Coombs' testing, haemoplasma and retroviral infections, and feline anaemia. METHODS: Haematology, Coombs' testing (including assessment of persistent autoagglutination) and selected infection testing (haemoplasma, feline leukaemia virus/feline immunodeficiency virus provirus) were performed in blood samples collected from 60 anaemic and 60 non-anaemic cats. RESULTS: No association between infection and anaemia or Coombs' positivity existed. Anaemic cats (21.7%) were significantly more likely than non-anaemic cats (0%) to have cold autoagglutination (P<0.0001), but significance (set at <or=0.0025 due to multiple testing) was not quite reached when Coombs' positivity was compared between anaemic (40.4% and 21.7% positive at 4 degrees C and 37 degrees C, respectively) and non-anaemic (20% and 3.3% positive, P=0.021 and P=0.004, at 4 degrees C and 37 degrees C, respectively) cats. Cats with immune-mediated haemolytic anaemia were significantly more likely to have persistent cold autoagglutination (P<0.0001) and be Coombs' positive at 37 degrees C with polyvalent (P<0.0001), immunoglobulin (Ig)G (P<0.0001) or any antiserum (P<0.0001). Haemoplasmas and retroviruses were uncommonly detected. CLINICAL SIGNIFICANCE: Cats suspected of having immune-mediated haemolytic anaemia should be evaluated for persistent autoagglutination at 4 degrees C as well as performing Coombs' testing at 37 degrees C, but positive results may occur in with other forms of anaemia. Testing for erythrocyte-bound antibodies should always be interpreted in parallel with documentation of haemolysis in anaemic cats.
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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 | 0.003 |
| 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".