Topographical distribution and radiographic pattern of lung lesions in canine eosinophilic bronchopneumopathy
Bibliographic record
Abstract
Objectives To evaluate the radiographic lung pattern and topographical distribution in canine eosinophilic bronchopneumopathy. Materials and Methods Medical records were retrospectively reviewed for dogs diagnosed with eosinophilic bronchopneumopathy. Lateral thoracic radiographs were examined for the presence of increased radiopacity, classification of pattern, topography of lung changes (cranioventral, perihilar, caudodorsal, caudoventral) and severity of pulmonary lesions. Results Forty‐four cases were identified with the Labrador retriever being the most commonly affected breed; there was a mean age of 5 years and an equal gender distribution. Coughing was the most common clinical sign. Circulating eosinophilia was present in 39% of dogs, with a mean peripheral eosinophilia of 5.1×10 9 cells/L and a mean bronchoalveolar lavage fluid eosinophilia of 40%. Eighty percent of dogs had an abnormal lung pattern in at least one of the four lung fields; the remaining had normal thoracic radiographs. The most common patterns were a bronchial and a bronchointerstitial pattern, with 41 and 89% distribution to the caudodorsal lung field, respectively. Clinical Significance A bronchial and bronchointerstitial pattern are the most common radiographic lung patterns seen in canine eosinophilic bronchopneumopathy with these patterns most frequently topographically distributed to at least the caudodorsal lung field. Furthermore, within the caudodorsal lung field, a bronchointerstitial pattern predominates. This radiographic and topographical finding may allow eosinophilic bronchopneumopathy to take precedence on a differential diagnoses list before confirmatory bronchoalveolar lavage fluid sampling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".