Evaluating pediatric advanced life support in emergency medical services with a performance and safety scoring tool
Bibliographic record
Abstract
INTRODUCTION: Pediatric out-of-hospital cardiac arrests (P-OHCA) are infrequent, have low survival rates, and often have poor neurologic outcomes. Recent evidence indicates that high-performance emergency medical service (EMS) care can improve outcomes. OBJECTIVES: To evaluate Pediatric Advanced Life Support (PALS) guideline performance in the out of hospital setting and introduce an easy-to-use tool that scores guideline compliance and patient safety. METHODS: We observed EMS teams responding to standardized pediatric resuscitation simulations. Teams were dispatched to a mock assisted living home for a choking 6-year-old with a complex medical history. The child manikin was presented as unconscious and apneic, with bradycardic pulse. Teams were expected to monitor vitals; initiate airway management and cardiopulmonary resuscitation (CPR); and establish vascular access and administer epinephrine based on PALS guidelines. We developed a tool to score the quality of care for critical tasks and had a clinical expert evaluate technical performance using blinded video review. RESULTS: We observed 34 EMS teams providing care in P-OHCA simulations. Teams were proficient at assessing vitals, using correct-sized equipment, intubation, and confirmation of tube placement. Teams were delayed in initiating positive pressure ventilation (PPV) and chest compressions. Many teams (53%) deviated from guidelines in chest compressions with 17 (50%) performing continuous compressions before establishing an advanced airway and one (3%) not performing compressions. Similarly, 20 (59%) teams deviated from medication guidelines with 12 (35%) failing to administer epinephrine, six (18%) underdosing, and two (6%) overdosing by more than 20%. CONCLUSION: EMS teams were successful in selecting the appropriate equipment but delayed initiating ventilations in a child with severe bradycardia. We also noted frequent use of continuous chest CC rather than the AHA recommended 15:2 ratio. We developed a scoring tool with time-based criteria that can be used to assess guideline compliance, individual performance, and/or educational effectiveness.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".