Delivery of medication by breath-actuated nebulizer (BAN) is similar when used with differing inhalation / exhalation ratios: A contrast to breath enhanced nebulizer (BEN) behavior
Bibliographic record
Abstract
RATIONALE: BANs only deliver medication during inhalation. BENs continue to deliver aerosol (at a lower rate) during exhalation. If the inspiratory/expiratory (I/E) ratio of a patient decreases in obstructive lung disease, drug delivery efficiency by BEN may reduce. We compared the delivery of a corticosteroid by both types of nebulizer in a lab study. METHODS: These nebulizer/table-top compressor systems (n=5/group) were evaluated: (a) AeroEclipse®-XL BAN/ Ombra® (TMI); (b) LC-Plus® BEN/Pari Boy®; (c) LC-Sprint® BEN/Pari Boy® SX (PARI Respiratory Equipment); (d) SideStream® Plus BEN/Inspiration® Elite (Philips Respironics). Each device was evaluated with 2 x 2.0-mL fill of 0.25 mg/mL budesonide (AstraZeneca). The nebulizer was connected to a simulator (ASL5000, IngMar Medical) mimicking adult (tidal volume=500-ml) tidal breathing, with I/E ratios of 1:1, 1:2 or 1:3. Emitted aerosol was captured by filter at 1-minute intervals until sputtering to determine total mass budesonide delivered ( TM bud ), as percentage of TM bud at I/E ratio=1:1. Budesonide assay was undertaken by HPLC-UV spectrophotometry. RESULTS: Average TM bud at extended I/E ratios as percentage of TM bud are in the Table. Nebulizer AeroEclipse®-XL LC-Plus® LC-Sprint® SideStream® Plus Type BAN BEN I/E ratio = 1:1 100.0 100.0 100.0 100.0 I/E ratio = 1:2 95.3 73.3 68.0 73.9 I/E ratio = 1:3 98.2 61.5 62.7 68.1 CONCLUSIONS: More consistent dose delivery was achieved by BAN. Clinicians should be aware of the opportunity to more confidently titrate patients to the lowest effective dose. The risk of potential under-dosing as disease progresses is also removed.
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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 | 0.002 |
| 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 | 0.001 | 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".