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Record W2761454751 · doi:10.1093/pch/pxx086.100

EFFECT OF EQUIPMENT ORGANIZATION ON NEONATAL RESUSCITATION UNDER SIMULATION CONDITIONS

2017· article· en· W2761454751 on OpenAlexaff
Brenda Hiu Yan Law, Po‐Yin Cheung, Michael O’Reilly, Caroline Fray, Georg M. Schmölzer

Bibliographic record

VenuePaediatrics & Child Health · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
Fundersnot available
KeywordsResuscitationMedicineCrossover studyProtocol (science)Randomized controlled trialNeonatal resuscitationMedical emergencyNeonatal intensive care unitStatistical analysisComputer scienceEmergency medicineSimulationStatisticsPediatricsSurgeryMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: The Neonatal Resuscitation Program (NRP) standardizes the steps needed during resuscitation of newborns. However, there are no recommendations on how to organize equipment to minimize errors or improve ergonomics. Adult and pediatric studies used large, comprehensive “code carts” and reported increases in speed of retrieval. However, this has not been studied with equipment sets used in the delivery room. OBJECTIVES: To compare performance in retrieving and using basic neonatal resuscitation equipment from an ergonomic equipment box versus a standard equipment bag in simulated scenarios. DESIGN/METHODS: NRP trained healthcare professionals (HCP) were recruited from a tertiary Neonatal Intensive Care Unit. Using a crossover design, participants were randomized to two simulated neonatal resuscitation scenarios (use of standard equipment bag followed by ergonomic equipment box and visa versa). The scenarios were video recorded to analyze the time needed to i) perform four equipment related tasks and ii) to complete the entire scenario. In a pilot trial a mean of 180s was needed to complete a scenario. Thirty participants were required to detect a 10% difference with a power of 0.8 and a significance of 0.05. Statistical analysis was performed using a paired t-test. A post-simulation survey examined user preference. RESULTS: We randomized 30 HCPs and observed four protocol violations (missing equipment), leaving 26 for analysis. Combined, HCPs had a mean scenario time of 192.6 ± 20.2s with the equipment bag and 176.1 ± 21.6s with the box, a difference of 16.5s (p<0.0001). HCPs (n=12) randomized to equipment bag followed by equipment box had a mean scenario time of 193.2 ± 16.1s and 163.7 ± 14.1s, respectively. Using the box, participants were faster by 29.5s (p<0.0001). In comparison, HCPs (n=14) randomized to equipment box then equipment bag had similar mean times of 186.7 ± 21.6s and 192.1 ± 23.7s, respectively. This likely represents a balance between the superiority of the box and the rehearsal effect of the second scenario. The post-simulation survey revealed preference by all participants for the equipment box. CONCLUSION: During neonatal resuscitation simulation, HCPs were able to retrieve equipment more quickly when it was ergonomically organized. Despite a lack of familiarity, all participants preferred the equipment box. Neonatal resuscitation equipment should be organized ergonomically to improve performance.(Fig 9, 10)

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)0.027
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.027
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.333
Teacher spread0.321 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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