Effects of positive end-expiratory pressure and 30% inspired oxygen on pulmonary mechanics and atelectasis in cats undergoing non-bronchoscopic bronchoalveolar lavage
Bibliographic record
Abstract
Objectives The objective of this study was to determine if modification of inspired oxygen concentration or positive end-expiratory pressure (PEEP) would alter bronchoalveolar lavage (BAL)-induced changes in pulmonary mechanics or atelectasis, as measured using ventilator-acquired pulmonary mechanics and thoracic CT. Methods Six experimentally asthmatic cats underwent anesthesia and non-bronchoscopic BAL, each under four randomized treatment conditions: 100% oxygen, zero PEEP; 30% oxygen, zero PEEP; 100% oxygen, PEEP 2 cmH 2 O; and 30% oxygen, PEEP 2 cmH 2 O. Pulse oximetry was used to estimate oxygen saturation (SpO 2 ). Ventilator-acquired pulmonary mechanics and thoracic CT scans were collected prior to BAL and at 1, 5 and 15 mins post-BAL. Results While receiving 100% oxygen, no cat had SpO 2 <91%. Some cats receiving 30% oxygen had decreased saturation immediately post-BAL (mean ± SD 70.8 ± 31%), but 6/8 of these had SpO 2 >90% by 1 min later. There was a significant increase in airway resistance and a decrease in lung compliance following BAL, but there was no significant difference between treatment groups. Cats receiving no PEEP and 30% oxygen conserved better aeration of the lung parenchyma in BAL-sampled areas than those receiving no PEEP and 100% oxygen. Conclusions and relevance Alterations in pulmonary mechanics or atelectasis may not be reflected by SpO 2 following BAL. The use of 30% inspired oxygen concentration failed to show any significant improvement in pulmonary mechanics but did diminish atelectasis. In some cats, it was also associated with desaturation of hemoglobin. The use of PEEP in this study did not show any effect on our outcome parameters. Further studies using higher PEEP (5–10 cmH 2 O) and intermediate inspired oxygen concentration (40–60%) are warranted to determine if they would confer clinical benefit in cats undergoing diagnostic BAL.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".