<i>In Vitro</i> Estimations of <i>In Vivo</i> Jet Nebulizer Efficiency Using Actual and Simulated Tidal Breathing Patterns
Bibliographic record
Abstract
In vivo aerosol delivery efficiency was estimated in vitro for two jet nebulizers using a breath monitor (Breathe!; Pari GmbH, Germany) and breath simulator (COMPAS; Pari GmbH) to reproduce subject tidal breathing patterns. The AeroEclipse (Trudell Medical International, Canada), a breath-actuated nebulizer, and the LC Star (Pari GmbH), a breath-enhanced nebulizer, were filled with levalbuterol HCl solution (Sepracor, USA) and operated with compressed O(2) at 8 lpm. Tidal breathing patterns of 20 adult subjects were digitally recorded with the Breathe! Breath Monitor. Subjects then breathed tidally from each nebulizer separately for 1 minute and to nebulizer dryness. Levalbuterol aerosol collected on filters placed between the nebulizer and mouth was chemically assayed to determine the inspired mass (IM), wasted mass (WM) and total emitted mass (TM). Measurements were repeated using the COMPAS Breath Simulator to simulate each subject's tidal breathing pattern. IM, WM, and TM measurements using actual versus simulated tidal breathing were highly comparable for each nebulizer, except the IM (p < 0.05) from LC Star measured at nebulizer dryness. Breath simulation was an inaccurate tool for estimating the time to nebulizer dryness as simulated measurements to nebulizer dryness took significantly longer than measurements preformed with actual tidal breathing (p < 0.001). While breath simulation provides an accurate in vitro tool for estimating in vivo aerosol delivery, it should not completely replace in vivo measurements until inherent limitations in simulator operation can be overcome to provide a more clinically realistic simulation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".