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Record W2509366393 · doi:10.1111/imj.31_13197

ASCIA‐P31: PRACTICE MAKES PERFECT: THE USE OF SIMULATION IN ANAPHYLAXIS TREATMENT TO IMPROVE CLINICAL SKILLS THAT CAN LEAD TO IMPROVED PATIENT OUTCOMES

2016· article· en· W2509366393 on OpenAlexaff
Di Edwards, Deryn Thompson

Bibliographic record

VenueInternal Medicine Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsCollege & Association of Registered Nurses of Alberta
Fundersnot available
KeywordsMedicineDebriefingAnaphylaxisSimulation trainingPreparednessSimulated patientNursingMedical emergencyAllergyMedical educationSimulation

Abstract

fetched live from OpenAlex

Anaphylaxis is a life-threatening, allergic emergency needing prompt, appropriate treatment. Nurses working in hospitals receive regular anaphylaxis management training. However, nurses working in non-acute environments, such as private or general practices, only receive update training at the employer's or nurse's own discretion. Simulation has been successfully used for updating anaphylaxis skills in nursing and medicine (Oleary et al. 2013; Mason & Lyons 2013) and ambulance staff (Lamers et al. 2014) enabling staff reflection. Such opportunities are rare for staff working outside acute environments. A pilot simulation exercise was held in a university nursing school practice-based simulation laboratory, during an Australian Allergy Nursing conference, to highlight gaps in nurses’ knowledge, improve their clinical experience and critical event management of anaphylaxis. Evaluation was undertaken by a pre-and post-event questionnaire. Twelve participants participated two 20 minute anaphylaxis simulations. Scenario 1 involved recognition and treatment of a 6 year old child who developed anaphylaxis to peanut in a community-based setting. The second involved recognition and treatment of a 55 year old female who experienced anaphylaxis in a hospital allergy clinic while undergoing bee-venom immunotherapy. Specialist Allergy Nurses facilitated the filmed simulation exercise. For 30 minutes prior to the simulation, participants also practiced with equipment discussing emergency situation, communication and decision making activities related to anaphylaxis. Debriefing and re-playing of the simulation recordings assisted participants to reflect on their participation, actions and learning. Nurses valued the opportunity to participate in the simulation environment. Common to both scenarios were team-work errors, delays in communicating, documenting and administering adrenalin. Nurses found the exercise identified and improved their skills in anaphylaxis management in a non-threatening environment and suggested it be incorporated in allergy programs annually.

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)0.008
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0180.007

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 head0.080
GPT teacher head0.413
Teacher spread0.333 · 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 designSimulation or modeling
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

Citations0
Published2016
Admission routes1
Has abstractyes

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