Pattern of Coombs’ test reactivity has diagnostic significance in dogs with immune‐mediated haemolytic anaemia
Bibliographic record
Abstract
OBJECTIVES: To investigate the clinical significance of the pattern of Coombs' test reactivity in dogs with immune-mediated haemolytic anaemia. METHODS: Sixty-five anaemic dogs with a positive Coombs' test were included. Coombs' testing was performed at 4 and 37 degrees C with polyvalent canine Coombs' reagent and antisera specific for each of canine immunoglobulin G, immunoglobulin M and complement factor C3. The impact of performing testing with only polyvalent antiserum at 37 degrees C was assessed. Chi-squared tests were used to compare Coombs' test reactivity in dogs with primary immune-mediated haemolytic anaemia (group A) and in dogs with concurrent/underlying disease (group B). Following Bonferroni correction, significance was set at P < or = 0.003. RESULTS: Eleven dogs would have been regarded as Coombs' negative had they been tested with polyvalent antiserum at 37 degrees C alone. Group A dogs were significantly more likely to be positive with polyvalent antiserum and/or anti-dog immunoglobulin G at 4 and/or 37 degrees C (P < or = 0.001) and tended to be less likely to be positive with anti-dog immunoglobulin M at 4 degrees C (P=0.040). CLINICAL SIGNIFICANCE: Testing of anaemic dogs with polyvalent Coombs' reagent at 37 degrees C was less sensitive than testing with monovalent reagents at 4 and 37 degrees C. The pattern of Coombs' test reactivity differed significantly between dogs with primary immune-mediated haemolytic anaemia and those with concurrent/underlying disease.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 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".