Comparison between manual aspiration via polyethylene tubing and aspiration via a suction pump with a suction trap connection for performing bronchoalveolar lavage in healthy dogs
Bibliographic record
Abstract
OBJECTIVE: To compare the diagnostic quality of bronchoalveolar lavage (BAL) fluid acquired from healthy dogs by manual aspiration via polyethylene tubing (MAPT) and via suction pump aspiration (SPA) with a suction trap connection. ANIMALS: 12 healthy adult Beagles. PROCEDURES: BAL was performed with bronchoscopic guidance in anesthetized dogs. The MAPT was performed with a 35-mL syringe attached to polyethylene tubing wedged in a bronchus via the bronchoscope's biopsy channel. The SPA was performed with 5 kPa of negative pressure applied to the bronchoscope's suction valve via a suction trap. The MAPT and SPA techniques were performed in randomized order on opposite caudal lung lobes of each dog. Two 1 mL/kg lavages were performed per site. Samples of BAL fluid were analyzed on the basis of a semiquantitative quality scale, percentage of retrieved fluid, and total nucleated and differential cell counts. Results were compared with Wilcoxon signed rank tests. RESULTS: Percentage of BAL fluid retrieved (median difference, 16.2%), surfactant score (median difference, 1), and neutrophil count (median difference, 74 cells/μL) were significantly higher for SPA than for MAPT. A higher BAL fluid epithelial cell score was obtained via MAPT, compared with that for samples obtained via SPA (median difference, 1). CONCLUSIONS AND CLINICAL RELEVANCE: Results indicated that in healthy dogs, SPA provided a higher percentage of BAL fluid retrieval than did MAPT. The SPA technique may improve the rate of diagnostic success for BAL in dogs, compared with that for MAPT. Further evaluation of these aspiration techniques in dogs with respiratory tract disease is required.
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 | 0.003 | 0.004 |
| 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 | 0.001 | 0.001 |
| 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".