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Record W4397043602 · doi:10.1101/2024.05.16.24307340

A qualitative study of emergency nurses’ perspectives on intranasal ketamine for procedural sedation in children

2024· preprint· en· W4397043602 on OpenAlexaffabout
David Wonnacott, Shannon D. Scott, Rachel Flynn, Samina Ali, Everly Van Der Vaart, Naveen Poonai

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsChildren’s Health Research InstituteLondon Health Sciences CentreWomen and Children’s Health Research InstituteUniversity of AlbertaWestern University
Fundersnot available
KeywordsKetamineSedationNasal administrationAnesthesiaMedicinePsychologyPharmacology

Abstract

fetched live from OpenAlex

ABSTRACT Purpose There is mounting evidence supporting a role for intranasal (IN) ketamine for procedural sedation in children due to its less invasive delivery. Drug administration and monitoring is largely performed by nurses and clinical uptake requires understanding their perceptions. We explored nursing perspectives of IN ketamine for procedural sedation in children to understand facilitators and barriers and inform institutional guidelines. Design and Methods From January to February, 2018, we conducted 2 focus groups with 8 registered nurses in a Canadian tertiary care paediatric ED. Following professional transcription, data were analyzed using an inductive qualitative approach. Results Seven of 8 participants had experience administering IN ketamine to children for procedural sedation. Nurses perceived that IN ketamine had the potential to reduce children’s distress and improve nursing resource use. Perceived barriers included: 1) uncertainty regarding sedation effectiveness and incorporation into institutional sedation protocols, 2) perceptions that IN ketamine produced a relatively lighter, slower-onset, and less titratable sedation, and 3) healthcare providers’ lack of familiarity with IN ketamine and reluctance to change their current approach to sedation. Conclusions We identified barriers to adoption of IN ketamine such as uncertainty regarding its pharmacodynamic properties, safety, and impact on workflow, along with facilitators such as fewer adverse events and nursing resources, and less procedural distress for children. Practice Implications Provider education should focus on IN ketamine’s pharmacodynamic properties and development of institutional sedation guidelines that define indications for use, support engagement of child life specialists, and operationalize the type and duration of monitoring requirements. CLINICIAN’S CAPSULE What is known about the topic? Intranasal ketamine is an emerging agent for procedural sedation and analgesia in the emergency department due to ease of administration. What did this study ask? What are paediatric nurses’ perspectives on intranasal ketamine for procedural sedation among children in the emergency department? What did this study find? Nurses identified advantages to intranasal ketamine but expressed considerable uncertainty regarding its pharmacodynamic properties and its incorporation into clinical practice. Why does this study matter to clinicians? Provider education may overcome some uncertainty and should focus on intranasal ketamine’s pharmacodynamic properties and incorporation into institutional sedation protocols. Meetings Pediatric Academic Societies (Baltimore, Maryland, April 30, 2019); Canadian Association of Emergency Physicians (Halifax, Nova Scotia, May 29, 2019); Canadian Paediatric Society (Toronto, Ontario, June 7, 2019)

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)0.018
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.008
Scholarly communication0.0040.005
Open science0.0020.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.405
Teacher spread0.358 · 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 designQualitative
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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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