Effect of a Cardiopulmonary Resuscitation Coach on Workload During Pediatric Cardiopulmonary Arrest: A Multicenter, Simulation-Based Study
Bibliographic record
Abstract
OBJECTIVES: Optimal cardiopulmonary resuscitation can improve pediatric outcomes but rarely is cardiopulmonary resuscitation performed perfectly despite numerous iterations of Basic and Pediatric Advanced Life Support. Cardiac arrests resuscitation events are complex, often chaotic environments with significant mental and physical workload for team members, especially team leaders. Our primary objective was to determine the impact of a cardiopulmonary resuscitation coach on cardiopulmonary resuscitation provider workload during simulated pediatric cardiac arrest. DESIGN: Multicenter observational study. SETTING: Four pediatric simulation centers. SUBJECTS: Team leaders, cardiopulmonary resuscitation coach, and team members during an 18-minute pediatric resuscitation scenario. INTERVENTIONS: National Aeronautics and Space Administration-Task Load Index. MEASUREMENTS AND MAIN RESULTS: Forty-one teams (205 participants) were recruited with one team (five participants) excluded from analysis due to protocol violation. Demographic data revealed no significant differences between the groups in regard to age, experience, distribution of training (nurse, physician, and respiratory therapist). For most workload subscales, there were no significant differences between groups. However, cardiopulmonary resuscitation providers had a higher physical workload (89.3 vs 77.9; mean difference, -11.4; 95% CI, -17.6 to -5.1; p = 0.001) and a lower mental demand (40.6 vs 55.0; mean difference, 14.5; 95% CI, 4.0-24.9; p = 0.007) with a coach (intervention) than without (control). Both the team leader and coach had similarly high mental demand in the intervention group (75.0 vs 73.9; mean difference, 0.10; 95% CI, -0.88 to 1.09; p = 0.827). When comparing the cardiopulmonary resuscitation quality of providers with high workload (average score > 60) and low to medium workload (average score < 60), we found no significant difference between the two groups in percentage of guideline compliant cardiopulmonary resuscitation (42.5% vs 52.7%; mean difference, -10.2; 95% CI, -23.1 to 2.7; p = 0.118). CONCLUSIONS: The addition of a cardiopulmonary resuscitation coach increases physical workload and decreases mental workload of cardiopulmonary resuscitation providers. There was no change in team leader workload.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".