Procedural sedation and its place in paediatric emergency medicine
Bibliographic record
Abstract
Procedural sedation is an integral part of emergency medicine (EM) practice in the USA, Canada, Australia and New Zealand. These countries have produced a large, robust literature supporting the safe and efficacious use of ketamine, propofol and other ED sedation agents for managing procedural pain and anxiety.1–3 In the UK and Ireland, EM and paediatric EM practitioners are striving to similarly establish procedural sedation as a fundamental part of their practice. McCoy et al describe, through a structured interview session with a group of EM consultants, the current issues impacting procedural sedation in the UK and the barriers to its adoption. Many of these same challenges and impediments were encountered in North America and Australia/New Zealand, and the lessons learned may be applicable and helpful in the UK and Ireland.4 As veterans of these challenges, here is our perspective. The capability of paediatric emergency physicians to administer timely procedural sedation directly benefits patients and their families by providing a safe, effective and efficient outpatient way of managing procedural pain and anxiety. Emergency physicians from North America, Australia and New Zealand reading the McCoy et al report will be surprised by the acceptance of hospitalisation as standard practice for management of simple forearm fractures in children, especially in the UK where EM is an established specialty. Such an approach transforms a brief ED procedure and a 30–90 min recovery into an overnight bed, an admitting paediatrician, a theatre room and an anaesthetist. Instead of promptly returning to the comforts of home, …
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 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".