Positive End-expiratory Pressure Increments during Anesthesia in Normal Lung Result in Hysteresis and Greater Numbers of Smaller Aerated Airspaces
Bibliographic record
Abstract
BACKGROUND: Although it is recognized that pulmonary hysteresis can influence the effects of positive end-expiratory pressure (PEEP), the extent to which expansion of previously opened (vs. newly opening) peripheral airspaces contribute to increased lung volume is unknown. METHODS: Following a recruitment maneuver, rats were ventilated with constant tidal volumes and imaged during ascending and descending ramps of PEEP. RESULTS: The authors estimated peripheral airspace dimensions by measuring the apparent diffusion coefficient of He in 10 rats. In a separate group (n = 5) undergoing a similar protocol, the authors used computerized tomography to quantify lung volume. Hysteresis was confirmed by larger end-inspiratory lung volume (mean ± SD; all PEEP levels included): 8.4 ± 2.8 versus 6.8 ± 2.0 ml (P < 0.001) and dynamic compliance: 0.52 ± 0.12 versus 0.42 ± 0.09 ml/cm H2O (P < 0.001) during descending versus ascending PEEP ramps. Apparent diffusion coefficient increased with PEEP, but it was smaller during the descending versus ascending ramps for corresponding levels of PEEP: 0.168 ± 0.019 versus 0.183 ± 0.019 cm/s (P < 0.001). Apparent diffusion coefficient was smaller in the posterior versus anterior lung regions, but the effect of PEEP and hysteresis on apparent diffusion coefficient was greater in the posterior regions. CONCLUSIONS: The authors' study results suggest that in healthy lungs, larger lung volumes due to hysteresis are associated with smaller individual airspaces. This may be explained by opening of previously nonaerated peripheral airspaces rather than expansion of those already aerated. Setting PEEP on a descending ramp may minimize distension of individual airspaces.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".