P.117 A systematic review on opioid free analgesic techniques for supratentorial craniotomies
Bibliographic record
Abstract
Background: Post-craniotomy pain can be severe and undermanaged. While opioids are the mainstay treatment, they have the potential to interfere with neurological monitoring. The objectives of this review are: 1) to identify measures to provide opioid-free analgesia 2) to compare the effectiveness of non-opioid to opioid analgesia in post-craniotomy pain. Methods: A comprehensive search of EMBASE, MEDLINE, and the Cochrane Central Registry of Controlled Trials (CENTRAL) databases was conducted for RCTs evaluating the effect of opioid vs non-opioid pain control strategies in patients undergoing supratentorial craniotomy. Results: The literature search yielded 462 citations, 5 RCTs that met the inclusion criteria for a total of 250 patients. Scalp infiltration/block was found to provide equivalent analgesia to morphine1 and fentanyl.2 Morphine was associated with slightly higher postoperative nausea and vomiting. Paracetamol was less likely to induce nausea and vomiting,3,4 but provided inadequate pain relief compared to nalbuphine,3 tramadol,3 morphine4 and sufentanil.4 Dexmedetomidine5 provided similar analgesia to remifentanil but did delay the time to first dose of rescue analgesia with similar side effects. Conclusions: Based on the limited number of RCTs comparing opioid to non-opioid techniques, no definite recommendations can be made with regards to the optimal management of post-craniotomy pain. Considerations should be made for use of multimodal analgesia-including adjuvant analgesics.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".