Pain Management in Children: Part 1 — Pain Assessment Tools and a Brief Review of Nonpharmacological and Pharmacological Treatment Options
Bibliographic record
Abstract
If pain is not treated quickly and effectively in children, it can cause long-term physical and psychological sequelae. Therefore, it is important for all health care providers to understand the importance of effective pain control in children. This article is divided into 2 parts: Part 1 reviews the pharmacotherapy of pain management in children and Part 2 will review the problems relating to the use of codeine in children, and the rationale for recommending morphine as the opioid of choice in the treatment of moderate to severe pain. There has been growing concern about codeine's lack of efficacy and increased safety concerns in its use in children. Due to the variability of codeine metabolism and unpredictable effects on efficacy and safety, The Hospital for Sick Children in Toronto, Ontario, no longer includes codeine or codeine-containing products on the regular hospital formulary and now recommends oral morphine as the agent of choice for the treatment of moderate to severe pain in children. A knowledge translation (KT) strategy was developed and implemented by the hospital's Pain Task Force to support this practice change.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".