American Society for Enhanced Recovery and Perioperative Quality Initiative Joint Consensus Statement on Perioperative Opioid Minimization in Opioid-Naïve Patients
Bibliographic record
Abstract
Surgical care episodes place opioid-naïve patients at risk for transitioning to new persistent postoperative opioid use. With one of the central principles being the application of multimodal pain interventions to reduce the reliance on opioid-based medications, enhanced recovery pathways provide a framework that decreases perioperative opioid use. The fourth Perioperative Quality Initiative brought together a group of international experts representing anesthesiology, surgery, and nursing with the objective of providing consensus recommendations on this important topic. Fourth Perioperative Quality Initiative was a consensus-building conference designed around a modified Delphi process in which the group alternately convened for plenary discussion sessions in between small group discussions. The process included several iterative steps including a literature review of the topics, building consensus around the important questions related to the topic, and sequential steps of content building and refinement until agreement was achieved and a consensus document was produced. During the fourth Perioperative Quality Initiative conference and thereafter as a writing group, reference applicability to the topic was discussed in any area where there was disagreement. For this manuscript, the questions answered included (1) What are the potential strategies for preventing persistent postoperative opioid use? (2) Is opioid-free anesthesia and analgesia feasible and appropriate for routine operations? and (3) Is opioid-free (intraoperative) anesthesia associated with equivalent or superior outcomes compared to an opioid minimization in the perioperative period? We will discuss the relevant literature for each questions, emphasize what we do not know, and prioritize the areas for future research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".