Safety Events in High Risk Prehospital Neonatal Calls
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to quantify and characterize patient safety events during high-risk neonatal transports in the prehospital setting. METHOD: We conducted a retrospective chart review of all "lights and sirens" ambulance transports of neonates ≤30 days old over a four-year period in a metropolitan area. Each case was independently reviewed for potential patient safety events that may have occurred in clinical assessment and decision making, resuscitation, airway management, fluid or medication administration, procedures performed, and/or equipment used. RESULTS: Twenty-six patients ≤30 days old were transported by ambulance using lights and sirens during the four-year study period. Overall, safety events occurred in 19 patients and severe safety events (potentially causing permanent injury or harm, including death) occurred in ten. The incidence of safety events related to medication administrations was 90% (70% severe), resuscitation 64.7% (47.1% severe), procedures 64.7% (35.3% severe), fluid administration 50% (25% severe), clinical assessment and decision making 50% (30.8% severe), airway management 47.6% (28.6% severe), equipment use 25.5% (10.0% severe), and systems processes 19.2% (7.7% severe). CONCLUSIONS: High-risk neonatal calls are infrequent and prone to a high incidence of serious patient safety events.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".