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Record W2933266449 · doi:10.1155/2019/4602651

Nasal Delivery Devices: A Comparative Study on Cadaver Model

2019· article· en· W2933266449 on OpenAlexaff
Antonio Moffa, Andrea Costantino, Vittorio Rinaldi, Lorenzo Sabatino, Eleonora M. C. Trecca, Peter Baptista, Paolo Campisi, Michele Cassano, Manuele Casale

Bibliographic record

VenueBioMed Research International · 2019
Typearticle
Languageen
FieldMedicine
TopicNasal Surgery and Airway Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineNasal cavityNasal sprayNasal vestibuleMucous membrane of noseSyringeBiomedical engineeringNasal administrationSurgeryAnatomy

Abstract

fetched live from OpenAlex

Nasal nebulization is a more effective method of delivering topical medication than nasal spray. The purpose of this study was to assess the deposition patterns of nebulization in delivering topical agents to the nasal cavities in the human cadaveric model using a color-based method. We have compared these following nasal devices: single-dose vial irrigation, syringe-irrigation, common nasal spray, Spray-sol, MAD nasal, and Rinowash nasal douche. Endoscopic images were recorded at six anatomical regions prior to and following each nasal device application and four reviewers evaluated the amount of surface area staining. At the nasal vestibule, the blue dye distribution achieved with Spray-sol was more extensive than nasal sprays. At inferior turbinate and nasal cavity floor, single dose vial, syringe, MAD nasal, Spray-sol, and Rinowash demonstrated a greater extent of dye distribution than nasal spray. At the middle turbinate, the average score of both Spray-sol and MAD nasal was significantly higher than other nasal investigated devices. At the nasopharynx, Spray-sol nebulization covers a surface significantly greater than other devices. Compared to traditional sprays, Spray-sol and MAD nasal provided a more effective method of delivering topical agents to the deeper and higher portions of the nasal cavities.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.264
GPT teacher head0.472
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations35
Published2019
Admission routes1
Has abstractyes

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