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Record W3106440509 · doi:10.1097/pcc.0000000000002623

Influence of Cardiopulmonary Resuscitation Coaching on Interruptions in Chest Compressions During Simulated Pediatric Cardiac Arrest*

2020· article· en· W3106440509 on OpenAlexaffabout
David Kessler, Zoe Grabinski, Lindsay N. Shepard, Sara I. Jones, Yiqun Lin, Jonathan P. Duff, Nancy M. Tofil, Adam Cheng

Bibliographic record

VenuePediatric Critical Care Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsAlberta Children's HospitalStollery Children's HospitalUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsCardiopulmonary resuscitationMedicineResuscitationDuration (music)CoachingEmergency medicineAnesthesiaMedical emergency

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine the impact of a cardiopulmonary resuscitation coach on the frequency and duration of pauses during simulated pediatric cardiac arrest. DESIGN: This is a secondary analysis of video data collected from a prospective multicenter trial. Forty simulated pediatric cardiac arrest scenarios (20 noncoach and 20 coach teams), each lasting 18 minutes in duration, were reviewed by three clinical experts to document events surrounding each pause in chest compressions. SETTING: Four pediatric academic medical centers from Canada and the United States. SUBJECTS: Two-hundred healthcare providers in five-member interprofessional resuscitation teams that included either a cardiopulmonary resuscitation coach or a noncoach clinical provider. INTERVENTIONS: Teams were randomized to include either a trained cardiopulmonary resuscitation coach or an additional noncoach clinical provider. MEASUREMENTS AND MAIN RESULTS: The frequency, duration, and associated factors with each interruption in chest compressions were recorded and compared between the groups with and without a cardiopulmonary resuscitation coach, using t tests, Wilcoxon rank-sum tests, or chi-squared tests, depending on the distribution and types of outcome variables. Mixed-effect linear models were used to explore the effect of cardiopulmonary resuscitation coaching on pause durations, accounting for multiple measures of pause duration within teams. A total of 655 pauses were identified (noncoach n = 304 and coach n = 351). Cardiopulmonary resuscitation-coached teams had decreased total mean pause duration (98.6 vs 120.85 s, p = 0.04), decreased intubation pause duration (median 4.0 vs 15.5 s, p = 0.002), and similar mean frequency of pauses (17.6 vs 15.2, p = 0.33) when compared with noncoach teams. Teams with cardiopulmonary resuscitation coaches are more likely to verbalize the need for pause (86.5% vs 73.7%, p < 0.001) and coordinate change of the compressors, rhythm check, and pulse check (31.7% vs 23.2%, p = 0.05). Teams with cardiopulmonary resuscitation coach have a shorter pause duration than non-coach teams, adjusting for number and types of tasks performed during the pause. CONCLUSIONS: When compared with teams without a cardiopulmonary resuscitation coach, the inclusion of a trained cardiopulmonary resuscitation coach leads to improved verbalization before pauses, decreased pause duration, shorter pauses during intubation, and better coordination of key tasks during chest compression pauses.

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)0.016
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.325
Teacher spread0.301 · 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 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
Published2020
Admission routes2
Has abstractyes

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