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Record W4312113298 · doi:10.29390/cjrt-2022-044

Optimal delivery of aerosolized medication to mechanically ventilated pediatric and neonatal patients: A scoping review

2022· review· en· W4312113298 on OpenAlexafffundvenue
Louise Chartrand, Victoria Ploszay, Sébastien Tessier

Bibliographic record

VenueCanadian Journal of Respiratory Therapy · 2022
Typereview
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsSt. Boniface HospitalChildren's Hospital Research Institute of ManitobaUniversity of Manitoba
FundersChildren's Hospital Research Institute of Manitoba
KeywordsCINAHLMedicineNebulizerAerosolizationMechanical ventilationIntensive care medicineMEDLINEPsychological interventionNursingInhalationAnesthesia

Abstract

fetched live from OpenAlex

Objectives: Delivering aerosolized medication to patients during mechanical ventilation is a common practice in respiratory therapy for adult, pediatric, and neonatal populations. However, aerosol delivery in pediatric populations is inconsistent and challenging, impacting how the drug is delivered. Some factors that influence drug delivery efficiency are directly under the purview of the clinician or therapist administering the drugs. However, excessive variability exists amongst clinicians and therapists working at the same site and between different sites. This review aims to systematically summarize the literature to identify current practice variations, identify common practices, and provide suggestions to guide future research in this area. In addition, this scoping review aims to identify the available evidence and knowledge gaps in the literature regarding the delivery of aerosolized medication to pediatric populations during mechanical ventilation. More specifically, the question that guided our research was: What are the best strategies for optimizing aerosol delivery of medication to pediatric patients, including neonates, while on mechanical ventilation? Methods: A scoping review, using the Joanna Briggs Institute methodology, was conducted until September 2022 in the CINAHL, EMBASE (Ovid), and Medline (Ovid) databases. Our initial search yielded 248 articles. After screening the titles, abstracts, and full text of the articles according to inclusion and exclusion criteria, five articles were analyzed. Results: We identified three main topics for discussion: the type of device used for administering aerosolized medication, appropriate mechanical ventilation settings, and optimal placement of the nebulizer delivery system. Conclusion: Of the three topics we intended to discuss, we only found enough evidence to suggest using mesh nebulizers to increase aerosol deposition. We found conflicting or outdated results for the other two topics. This demonstrates a significant gap in the literature since aerosol medications are routinely administered to mechanically ventilated neonatal and other pediatric patients.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.330
Teacher spread0.276 · 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 designOther design
Domainnot available
GenreReview

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

Citations3
Published2022
Admission routes3
Has abstractyes

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