Development and expansion of a pediatric transitional pain service to prevent complex chronic pain
Bibliographic record
Abstract
The prevention of chronic pain is a key priority in North America and around the world. A novel pediatric Transitional Pain Service (pTPS) at the Hospital for Sick Children was established to address four main areas of need, which the authors will describe in more detail: (1) provide comprehensive multi-modal pain management and prevention techniques to children at-risk for the development of chronic pain, (2) provide opioid stewardship for children at-risk for chronic pain and their families at home after discharge, (3) facilitate continuity of pain care for children across transitions between inpatient and outpatient care settings, and (4) support caregivers to manage their child's pain at home. The pTPS works with healthcare providers, patients, and their families to address these areas of need and improve quality of life. Furthermore the service fills the gap between inpatient acute pain services and outpatient chronic pain services (accessible only once pain has persisted for >3 months). In pediatric patients who experience pain in hospital and who have been prescribed opioids, discharge to home or rehabilitation may represent a vulnerable time in which pain may persist and during which analgesic requirements may change. This offers an important opportunity to address and prevent the development of chronic pain, and to monitor opioids while ensuring alternative pain therapy is available. The authors will outline risk factors for persistent postsurgical pain, the development and implementation of a pTPS, present initial clinical outcomes andsuggest areas for future research in this evolving area of care.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".