P279 Priming of a non-conducting valved holding chamber (vhc) may result in inconsistent medication delivery
Bibliographic record
Abstract
Introduction and Objectives Priming VHCs with several actuations of medication before use may be an established practice to prepare the spacer before use. However this practice can have a significant influence on subsequent medication delivery. The present study set out to test the hypothesis that priming is not effective, or better than the use of anti-static materials. Methods The following VHCs, each with mouthpiece as patient interface (n=5 devices/group) were evaluated: AeroChamber Plus Flow-Vu Antistatic VHC (AC +FV AVHC); AeroChamber Plus; Volumatic…; Able Spacer 2…; Anti-Static Compact Space Chamber plus…. Each VHC was connected via a filter holder to a vacuum source operated at 28.3 L/min, evaluated with a pMDI (Flovent 125 µg, FP) and the Emitted Mass of FP (EMFP) determined by HPLC-UV assay. The following sequence of testing was conducted: 1) Test VHC immediately after removal from packaging (no pre-treatment) and evaluate EMFP following one actuation. 2) Supply two more actuations into the same VHC and evaluate EMFP (representing 3 actuations of priming).3) Deliver 17 more actuations into the same VHC and evaluate EMFP (representing priming of 20 actuations). 4) Clean VHC, then repeat part (1) (representing pre-conditioning by washing as an alternative to priming). Results The behaviour of EMFP (mean ±SD) with VHC type is summarised in figure 1. Conclusions Clinicians should be aware that priming of VHCs Results in inconsistent medication delivery, and is wasteful of medication.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".