A novel device for delivery of intranasal particulate medication: a pilot study
Bibliographic record
Abstract
BACKGROUND: Intranasal medication delivery for allergic rhinitis (AR) is considered a mainstay of therapy but is hampered by poor compliance. Among reasons given are unpleasant sensations associated with spray penetration into the pharynx. Our objective was to study a novel method of particle delivery to the nose that would abrogate these issues. METHODS: This was a double-blind, randomized study. Subjects who met study criteria underwent intranasal particle delivery using a novel device (Trivair Nasal Deposition System; Trimel Pharmaceuticals, Toronto, Canada) that delivered anhydrous lactose particles into the nose via a transoral air puff (thus elevating soft palate and blocking the nasopharynx). Subjects had nostrils randomized into 4 groups (particle sizes 5 μm and 50 μm × doses 12.5 mg and 25 mg). Particle deposition was assessed at 1 minute, 10 minutes, and 30 minutes on the inferior turbinate, middle turbinate, and nasopharynx, respectively, using high-definition endoscopic photography. Each image was compared using an expert blinded 2-person panel for percentage particles remaining. Nonparametric data was assessed using the Wilcoxon signed-rank test via Strata software. RESULTS: Twelve nostrils in total met study criteria. The results showed no difference in effectiveness of nasal particle retention between the groups based on particle size or dose. No particles entered the nasopharynx or oropharynx. CONCLUSION: This study provides proof-of-principle data that the Trivair Nasal Deposition System is effective at retaining medication in the nose without pharyngeal penetration. Larger studies on this device are warranted.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".