Procedural Pediatric Sedation by Nurses: Available, Competent, and Safe
Bibliographic record
Abstract
Sedation and/or analgesia are standard of care for pediatric patients during painful intervention or medical imaging requiring immobility. Physician availability is frequently insufficient to allow for all procedural sedation. A nurse-led sedation program was created at the Centre Hospitalier Universitaire de Sherbrooke (CHUS) to address this problem. Objective. To evaluate the effectiveness and the safety of our program. Methods. A retrospective study of all the procedural sedations done over one year was performed. Complications were separated in four categories: (1) major complications (call for help; unexpected admission, aspiration, and code); (2) reportable sedation events (oxygen saturation <90%, bradycardia (more than 2 SD below normal for the age of the child), and hypotension (more than 2 SD below normal for the age of the child); (3) difficult sedation (agitation, inadequate sedation, and failure to perform the procedure), (4) minor complications. Results. 448 patients, 249 boys and 199 girls; received sedation for 555 procedures. Overall, 78% (432) of interventions were successfully accomplished: 0% of major complications, 8% of reportable sedation events; 5% of difficult sedation; 9% of minor complications. Conclusion. Our nurse-led sedation program compares favorably to other similar systems.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".