Causes for Pauses During Simulated Pediatric Cardiac Arrest
Bibliographic record
Abstract
OBJECTIVES: Pauses in cardiopulmonary resuscitation negatively impact clinical outcomes; however, little is known about the contributing factors. The objective of this study is to determine the frequency, duration, and causes for pauses during cardiac arrest. DESIGN: This is a secondary analysis of video data collected from a prospective multicenter trial. Twenty-six simulated pediatric cardiac arrest scenarios each lasting 12 minutes in duration were analyzed by two independent reviewers to document events surrounding each pause in chest compressions. SETTING: Ten children's hospitals across Canada, the United, and the United Kingdom. SUBJECTS: Resuscitation teams composed of three healthcare providers trained in cardiopulmonary resuscitation. INTERVENTIONS: A simulated pediatric cardiac arrest case in a 5 year old. MEASUREMENTS AND MAIN RESULTS: The frequency, duration, and associated factors for each pause were recorded. Communication was rated using a four-point scale reflecting the team's shared mental model. Two hundred fifty-six pauses were reviewed with a median of 10 pauses per scenario (interquartile range, 7-12). Median pause duration was 5 seconds (interquartile range, 2-9 s), with 91% chest compression fraction per scenario (interquartile range, 88-94%). Only one task occurred during most pauses (66%). The most common tasks were a change of chest compressors (25%), performing pulse check (24%), and performing rhythm check (15%). Forty-nine (19%) of the pauses lasted greater than 10 seconds and were associated with shock delivery (p < 0.001), performing rhythm check (p < 0.001), and performing pulse check (p < 0.001). When a shared mental model was rated high, pauses were significantly shorter (mean difference, 4.2 s; 95% CI, 1.6-6.8 s; p = 0.002). CONCLUSIONS: Pauses in cardiopulmonary resuscitation occurred frequently during simulated pediatric cardiac arrest, with variable duration and underlying causes. A large percentage of pauses were greater than 10 seconds and occurred more frequently than the recommended 2-minute interval. Future efforts should focus on improving team coordination to minimize pause frequency and duration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".