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Record W2799851200 · doi:10.2147/ccid.s162724

Current trends in needle-free jet injection: an update

2018· review· en· W2799851200 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Cosmetic and Investigational Dermatology · 2018
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvancements in Transdermal Drug Delivery
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsMedicineInjectorDrug deliveryJet (fluid)Biomedical engineeringSurgeryMedical physicsNanotechnologyMaterials scienceMechanicsMechanical engineering

Abstract

fetched live from OpenAlex

BACKGROUND: Jet injection can be defined as a needle-free drug delivery method in which a high-speed stream of fluid impacts the skin and delivers a drug. Despite 75 years of existence, it never reached its full potential as a strategic tool to deliver medications through the skin. OBJECTIVE: The aim of this review was to evaluate and summarize the evolution of jet injection intradermal drug delivery method including technological advancements and new indications for use. METHODS: A review of the literature was performed with no limits placed on publication date. RESULTS: Needleless injectors not only reduce pain during drug delivery but also confine the drug more evenly in the dermis. Understanding skin properties of the injection site is a key factor to obtain optimal results as well as setting the right parameters of the jet injector. Until the advent of disposable jet injectors/cartridges, autoclaving of the injector remains the only reliable method to eliminate the risk of infection. Needle-free intradermal injection using corticosteroids and/or local anesthetics is well documented with promising indications being developed. LIMITATIONS: Limitations of the review include low-quality evidence, small sample sizes, varying treatment parameters, and publication bias. CONCLUSION: New developments may help reconsider the use of jet injection technology. Future studies should focus on measurable optimized parameters to insure a safe and effective outcome.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.954
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.372
GPT teacher head0.558
Teacher spread0.186 · 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