Perioperative Methadone for Spine Surgery: A Scoping Review
Bibliographic record
Abstract
Complex spine surgery is associated with significant acute postoperative pain. Methadone possesses pharmacological properties that make it an attractive analgesic modality for major surgeries. This scoping review aimed to summarize the evidence for the perioperative use of methadone in adults undergoing complex spine surgery. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). A search was performed using MEDLINE, CINAHL, Cochrane Library, Scopus, Embase, and Joanna Briggs between January 1946 and April 2023. The initial search identified 317 citations, of which 12 met the criteria for inclusion in the review. There was significant heterogeneity in the doses, routes of administration, and timing of perioperative methadone administration in the included studies. On the basis of the available literature, methadone has been associated with reduced postoperative pain scores and reduced postoperative opioid consumption. Though safety concerns have been raised by observational studies, these have not been confirmed by prospective randomized studies. Further research is required to explore optimal methadone dosing regimens, the potential synergistic relationships between methadone and other pharmacological adjuncts, as well as the potential long-term antinociceptive benefits of perioperative methadone administration.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".