P278 Assessing different valved holding chambers (vhc) with facemask for delivered mass to carina with inhaled corticosteroid by pressurised metered-dose inhaler (pmdi)
Bibliographic record
Abstract
Introduction and Objectives Laboratory evaluation of VHC-facemask add-ons is ideally undertaken simulating conditions of use. We report a study in which such devices for small child use were evaluated using an anatomical face-model and upper airway commensurate with that of a 4 year old child. Methods A number of VHCs with facemask (n=3 devices/group) were evaluated using an anatomical face-model and upper airway commensurate with that of a 4 year old child. Each VHC was prepared to manufacturer instructions, then evaluated by breathing simulator (ASL5000), mimicking a short coordination delay of 2 s followed by tidal breathing (tidal volume (Vt)=155 mL, I:E ratio=1:2, rate=25 cycles). The facemask was attached to ADAM-III small child model. The airway was coupled directly to the breathing simulator via a filter below its exit to capture drug particles that would penetrate as far as the carina in a real patient. 5-actuations of fluticasone propionate (50 µg, FP) were delivered at 30 s intervals. FP recovered from various locations in the aerosol pathway was subsequently assayed by HPLC-UV spectrophotometry. Results Distribution of recovered FP from each type of VHC is summarised in Table 1. Conclusions Significantly more FP was delivered to the model ‘carina’ from the AC Plus VHC with child mask (p<0.001), the increased mass counterbalanced by decreased retention of medication within the VHC. It is important that clinicians are aware that large differences in delivery efficiency may exist when a facemask is present.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".