Histologic patterns of chronic interstitial lung disease in dogs
Bibliographic record
Abstract
Chronic interstitial lung disease (cILD) is uncommon in dogs and little is known of the pathogenesis, apart from the condition in West Highland White Terriers. This study aimed to characterize histologic lesions of canine cILD, compare the lesions and clinical features, and classify the histopathologic patterns according to criteria used in humans. The study included 24 postmortem cases of subacute or chronic ILD in >6-month-old dogs with respiratory signs. Histologic lung lesions included attenuated bronchiolar epithelium, alveolar edema, type II pneumocyte proliferation, fibrosis of alveolar septa, fibrin or fibrous tissue within alveoli or bronchioles, and hyaline membranes. Of the 24 cases, 8 were classified as organizing diffuse alveolar damage, 4 as organizing pneumonia, and 3 as acute fibrinous and organizing pneumonia; 9 were unclassifiable and considered as nonspecific interstitial lung disease. None fulfilled criteria for usual interstitial pneumonia. Potential causes included aspiration of gastric or foreign material, prior acute respiratory distress syndrome, or failed healing of pneumonia. Left-sided heart failure was identified in 12 of 24 cases but was not considered to directly cause the interstitial lung lesions. Gross lesions of cor pulmonale were associated with organizing pneumonia and longer clinical duration. The cases had diverse histologic lesions and patterns of lung fibrosis, but the results suggested that these may represent divergent responses to overlapping causes of lung injury rather than distinct diseases. These findings clarify the pathogenesis of cILD in dogs, the mechanisms of initial damage, and the future development of approaches to delay or predict disease progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".