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Record W1935662762 · doi:10.4187/respcare.06511244

A Method for Increasing Jet Nebulizer Delivery Efficiency for Aerosol Drug Delivery in Ventilated Newborns: An In Vitro Study

2006· article· en· W1935662762 on OpenAlexaff
Michael C. Quong, Bernard Thébaud, Warren H. Finlay

Bibliographic record

VenueRespiratory Care · 2006
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNebulizerAerosolizationMedicineAerosolTidal volumeAnesthesiaInhalationRespiratory systemInternal medicineMeteorology

Abstract

fetched live from OpenAlex

BACKGROUND: A substantial percentage of the aerosol produced by a nebulizer is lost down the expiratory limb of the ventilator circuit. We describe a method for the capture, return, and re-aerosolization of that undelivered aerosol. METHODS: We designed an expiratory-limb setup in which an "entraining jet" of gas accelerates unused aerosol and propels it toward an impaction surface. The deposited solution is then returned to the nebulizer reservoir via a feedback tube. As a result, more of the initial dose is delivered to the patient. The fraction of the dose delivered to a filter connected to a passive neonatal test lung was measured with and without the aerosol-recycling components activated. We used a deltaP (difference between the peak inspiratory pressure and the positive-end-expiratory pressure) of approximately 7.5 cm H2O, tidal volume of approximately 6 mL, respiratory rate of 40 breaths/min, and an inspiratory-expiratory ratio of 1:2.3. RESULTS: There was a statistically significant improvement with the feedback return to the reservoir, with up to nearly 60% more aerosol delivered. CONCLUSION: This improvement in aerosol delivery is encouraging, but more comprehensive studies are needed before such a device could be implemented clinically.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.316
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2006
Admission routes1
Has abstractyes

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