Bronchoalveolar lavage hemosiderosis in dogs and cats with respiratory disease
Bibliographic record
Abstract
BACKGROUND: Hemosiderophages can be found in bronchoalveolar lavage samples and have been reported in association with a wide range of respiratory and cardiovascular disorders in cats and humans. OBJECTIVES: This study aimed to retrospectively evaluate the presence of hemosiderin in canine and feline bronchoalveolar lavage (BAL) samples. It also aimed to examine the association of BAL hemosiderin with signalment, clinical signs, and historical disease prior to BAL, with prior transthoracic fine-needle aspiration (FNA), with bronchoalveolar lavage duration, and with cytologic interpretation. METHODS: The medical records of dogs and cats with respiratory disease that underwent BAL between 2007 and 2016 were reviewed. Appropriate medical information and BAL results were available from 171 dogs and 34 cats. Cases were assigned to four disease categories based on BAL cytologic findings: pneumonia, inflammatory disease, neoplasia, or normal airways. The degree of hemosiderosis was classified based on a semi-quantitative scoring scale. Exact logistic regression analysis was used to evaluate the relationship between risk factors and the presence of BAL hemosiderosis on cytology. RESULTS: Hemosiderin was identified in 13/171 (7.6%) canine samples and 18/34 (52.9%) feline samples. Cats were 13.33 times more likely to have pulmonary hemosiderosis on bronchoalveolar lavage cytology compared with dogs (P < 0.001). Increased respiratory rates, prolonged bronchoalveolar lavage times, concurrent transthoracic FNAs, and cytologic diagnoses were associated with an increased risk of hemosiderosis in dogs. No specific risk factors associated with pulmonary hemosiderosis in cats were identified. CONCLUSIONS: Hemosiderosis is more common in BAL samples from cats than from dogs and is associated with a diverse range of disease conditions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".