Usage of spacers in respiratory laboratories and the delivered salbutamol dose of spacers available in Australia and New Zealand
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Purchase and disinfection costs together with medication delivery factors may influence the choice of drug delivery options. This study assessed salbutamol delivery habits used in respiratory laboratories and quantified the delivered salbutamol dose of locally available spacers. METHODS: An online survey was used to obtain data on disinfection processes, costs and delivery device choices. The delivered dose of six commercial spacers was assessed. Particle size distribution of salbutamol (Ventolin, GSK, 100µg/actuation) from six spacers of each type was measured by quantifying the amount of drug (µg) deposited on each stage of an Anderson Cascade Impactor (ACI) using UV spectrophotometry. Clinical conditions were simulated using a flow volume simulator (FVS) and delivery of salbutamol via a pressurized metered dose inhaler and spacer to a low-resistance filter was measured. RESULTS: Fifty survey responses were obtained, with 37 (74%) using ≥1 type of spacer of which 92% processed single use spacers. The most commonly used spacers were Volumatic (n=24), Breath-a-tech (n=8) and Space Chamber (n=7). The median disinfection cost was $2.45. Delivered salbutamol dose varied significantly and ranged from 16.98 to 38.28 µg with the ACI and 22.56 to 58.82 µg with the FVS. Using the FVS, small-volume spacers delivered similar doses (22.56 to 28.46 µg), while large-volume spacers delivery was more varied (24.31 to 58.82 µg). CONCLUSIONS: The majority of respiratory laboratories had not updated re-processing policies to comply with new regulations. The delivered salbutamol dose varied significantly and this might effect the choice of preferred spacer type.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 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".