Effects of High-Frequency Chest Wall Oscillation on Pleural Pressure and Oscillated Flow
Bibliographic record
Abstract
The effectiveness of high-frequency chest wall oscillation (HF-CWO) is directly related to the level of oscillated flow (osc) in the airways. We used the Vest system to investigate the effects of HFCWO on chest wall and pleural pressures and we correlated these pressures to the resultant osc. We also compared the latest HFCWO device with it predecessor. Different combinations of vest inflation pressure (background pressure) and oscillation frequency were randomly applied to 10 healthy volunteers. Chest wall pressure was determined using an air-filled bag under the vest and pleural pressure was estimated using an esophageal balloon. Reverse plethysmography was used to measure osc at the mouth and a spirometer was used to measure changes in end-expired lung volume. We found a significant correlation between chest wall and pleural pressure with approximately one-third of the chest wall pressure transmitted into the pleural space. Mean esophageal pressure remained negative at all background pressure/frequency combinations. There was a significant correlation (p<0.0001) between the esophageal pulse pressure and osc, which was highest at 15Hz regardless of the background pressure. The end-expired lung volume correlated with mean chest wall pressure. There was no significant difference between the two Vest systems. Since osc dictates the effectiveness of HFCWO and since osc is dependent on esophageal pulse pressure, which in turn is dependent on chest wall pulse pressure, it follows that the effectiveness of HFCWO is influenced by the ability to generate an effective chest wall pulse pressure.
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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 | 0.003 |
| 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) | 0.001 | 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".