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Record W4364354033 · doi:10.1542/peds.2022-059839

Real-Time Intubation and Ventilation Feedback: A Randomized Controlled Simulation Study

2023· article· en· W4364354033 on OpenAlexaff
Robyn Dvorsky, Franziska Rings, Katharina Bibl, Lisa Roessler, Lisa Kumer, Philipp Steinbauer, Hannah Schwarz, Valentin Ritschl, Georg M. Schmölzer, Angelika Berger, Tobias Werther, M. Wagner

Bibliographic record

VenuePEDIATRICS · 2023
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
Fundersnot available
KeywordsSupervisorMedicineRandomized controlled trialIntubationAnesthesiaFree accessSurgeryComputer science

Abstract

fetched live from OpenAlex

BACKGROUNDS: This study aimed to determine the best educational application of a respiratory function monitor and a video laryngoscope. METHODS: This study was a randomized controlled simulation-based trial, including 167 medical students. Participants had to execute ventilation and intubation maneuvers on a newborn manikin. Participants were randomized into 3 groups. In group A (no-access), the feedback devices were not visible but recording. In group B (supervisor-access), the feedback devices were visible to the supervisor only. In group C (full-access), both the participant and the supervisor had visual access. RESULTS: The two main outcome variables were the percentage of ventilations within the tidal volume target range (4-8mL/kg) and the number of intubation attempts. Group C achieved the highest percentage of ventilations within the tidal volume target range (full-access 63.6%, supervisor-access 51.0%, no-access 31.1%, P < .001) and the lowest mask leakage (full-access 34.9%, supervisor-access 46.6%, no-access 61.6%; A to B: P < .001, A to C: P < .001, B to C: P = .003). Overall, group C achieved superior ventilation quality regarding primary and secondary outcome measures. The number of intubation attempts until success was lowest in the full-access group (full-access: 1.29, supervisor-access: 1.77, no-access: 2.43; A to B: P = .001, A to C: P < .001, B to C: P = .015). CONCLUSIONS: Our findings confirm that direct visual access to feedback devices for supervisor and trainees alike considerably benefits outcomes and can contribute to the future of clinical education.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.355
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations18
Published2023
Admission routes1
Has abstractyes

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