Valved holding chambers (VHCs) can have different medication delivery performance as a function of delay interval following actuation of the pressurized metered dose inhaler (pMDI)
Bibliographic record
Abstract
RATIONALE: VHCs are prescribed for patients who cannot coordinate inhalation with actuation of a pMDI. Performance of these add-on devices as a function of delayed inhalation is therefore critical. The present study explored the in vitro performance of three different anti-static VHCs, simulating 5 s and 10 s delays. METHODS: 5 actuations of Seretide® 250µg fluticasone propionate (FP)/25µg salmeterol xinafoate (SX) (GSK) were delivered to AeroChamber Plus* Anti-Static VHC with Flow-Vu* IFI (( AC-Plus ) Trudell Medical International), OptiChamber® Diamond® VHC (( OD ) Philips Respironics) and Vortex™ (( Vortex ) PARI Respiratory Equipment) non electrostatic VHC (n=5 devices/group). Each VHC was used out-of-package and connected to an Andersen Mk II cascade impactor operated at 28.3 L/min. A proprietary apparatus enabled the required delay interval to be simulated. Recovered FP and SX were assayed using HPLC-UV spectrophotometry. RESULTS: Measures (mean ± SD) of therapeutically beneficial fine particle mass < 4.7 µm aerodynamic diameter (FPM <4.7 µm ) are summarized in the table. VHC type Seretide® component Delay (s) FPM<4.7 µm (µg/actuation) AC Plus FP 5 88.2 ± 5.6 10 78.3 ± 6.7 SX 5 8.6 ± 0.6 10 7.3 ± 0.5 OD FP 5 63.8 ± 7.8 10 48.6 ± 9.3 SX 5 6.2 ± 0.9 10 4.7 ± 0.8 Vortex FP 5 67.4 ± 9.7 10 47.8 ± 8.1 SX 5 7.0 ± 1.0 10 4.7 ± 0.8 CONCLUSIONS: FPM was significantly greater using the AC-Plus VHC compared to the OD and Vortex VHCs for both components at both time delays (1-way ANOVA, p ≤ 0.002). The clinical impact of potential under-dosing with poorly coordinated patients should be considered when selecting a VHC.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".