Dry Powder Inhaler Delivery of Tobramycin in <i>In Vitro</i> Models of Tracheostomized Children
Bibliographic record
Abstract
BACKGROUND: Pediatric tracheostomies are not uncommon and aerosols allow for targeted lung therapy. However, there is little literature that quantifies aerosol delivery through tracheostomies. Nebulizers are commonly used in delivering tobramycin, but there are drawbacks, for example, time burden. Dry powder inhalers (DPIs) can deliver higher payloads in less time. However, no data exist assessing DPIs with tracheostomies. OBJECTIVE: (LC Plus). METHODS: In vitro tracheostomized models of a 6- and 12-year-old trachea were created. Tobramycin aerosol was delivered to the models using either the LC Plus or Podhaler and captured on a filter at the trachea's distal end. A colorimetric tobramycin assay was used to quantify the amount. Three devices of each type were tested in triplicate to ensure repeatability. RESULTS: A total of 36 runs were completed and showed that the Podhaler was more efficient compared with the LC Plus. Mass and percentage of nominal dose, mean ± standard deviation (LC Plus vs. Podhaler with single capsule), was 72.4 ± 11.1 mg (24.1% ± 3.7%) versus 24.2 ± 2.4 mg (86.6% ± 8.7%); p < 0.001. CONCLUSIONS: The study's results show that the Podhaler was significantly more efficient compared with the LC Plus, and three Podhaler capsules delivered approximately the same amount of drug as the Tobramycin inhalation solution. These results suggest that Podhaler's tobramycin delivery is a feasible option in tracheostomized pediatric patients and a clinical study is warranted.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".