Survey of Sedation and Analgesia Practice Among Canadian Pediatric Critical Care Physicians*
Bibliographic record
Abstract
BACKGROUND: Despite the fact that almost all critically ill children experience some degree of pain or anxiety, there is a lack of high-quality evidence to inform preferred approaches to sedation, analgesia, and comfort measures in this environment. We conducted this survey to better understand current comfort and sedation practices among Canadian pediatric intensivists. METHODS: The survey was conducted after a literature review and initial focus groups. The survey was then pretested and validated. The final survey was distributed by email to 134 intensivists from 17 PICUs across Canada using the Research Electronic Data Capture system. RESULTS: The response rate was 73% (98/134). The most commonly used sedation scores are Face, Legs, Activity, Cry, and Consolability (42%) and COMFORT (41%). Withdrawal scores are commonly used (65%). In contrast, delirium scores are used by only 16% of the respondents. Only 36% of respondents have routinely used sedation protocols. The majority (66%) do not use noise reduction methods, whereas only 23% of respondents have a protocol to promote day/night cycles. Comfort measures including music, swaddling, soother, television, and sucrose solutions are frequently used. The drugs most commonly used to provide analgesia are morphine and acetaminophen. Midazolam and chloral hydrate were the most frequent sedatives. CONCLUSION: Our survey demonstrates great variation in practice in the management of pain and anxiety in Canadian PICUs. Standardized strategies for sedation, delirium and withdrawal, and sleep promotion are lacking. There is a need for research in this field and the development of evidence-based, pediatric sedation and analgesia guidelines.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".