Opioid reduction and enhanced recovery in orthopaedic surgery (OREOS): A feasibility randomized controlled trial in knee replacement patients
Bibliographic record
Abstract
Background: Total knee arthroplasties are the second most common surgery in Canada. Most patients recover well, but 20% or more still suffer from persistent pain and opioid use. Though opioids are an important part of perioperative pain management, their potential for long-term adverse effects is well recognized. Limiting opioids may be insufficient to overcome the issue of opioid overuse. Pain and opioid use are highly linked, so an effective alternative needs to address both issues. Objectives: The principal objective of this pilot trial is to assess the feasibility. The clinical objectives are to determine the effects of a multicomponent care pathway on opioid-free pain control, persisting pain and opioid use, functional knee outcomes, quality of life, and return to function. Methods: We will include adult patients scheduled for primary elective total knee arthroplasty. Patients in the intervention group will undergo a multicomponent intervention pathway that will be facilitated by an intervention coordinator linking each patient and their surgical/ perioperative team. The interventional pathway will include (1) preoperative education on pain and opioid use, (2) preoperative risk identification and mitigation using cognitive behavioral skills, (3) personalized postdischarge analgesic prescriptions, and (4) continued support for pain control and recovery up to 8 weeks. Patients in the control group will receive the usual care at their institution. Discussion: NCT04968132 (informed consent/ research ethics board statement).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".