Perioperative Dextromethorphan as an Adjunct for Postoperative Pain
Bibliographic record
Abstract
BACKGROUND: N-methyl-D-aspartate receptor antagonists have been shown to reduce perioperative pain and opioid use. The authors performed a meta-analysis to determine whether the use of perioperative dextromethorphan lowers opioid consumption or pain scores. METHODS: PubMed, Web of Science, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Pubget, and EMBASE were searched. Studies were included if they were randomized, double-blinded, placebo-controlled trials written in English, and performed on patients 12 yr or older. For comparison of opioid use, included studies tracked total consumption of IV or intramuscular opioids over 24 to 48 h. Pain score comparisons were performed at 1, 4 to 6, and 24 h postoperatively. Difference in means (MD) was used for effect size. RESULTS: Forty studies were identified and 21 were eligible for one or more comparisons. In 848 patients from 14 trials, opioid consumption favored dextromethorphan (MD, -10.51 mg IV morphine equivalents; 95% CI, -16.48 to -4.53 mg; P = 0.0006). In 884 patients from 13 trials, pain at 1 h favored dextromethorphan (MD, -1.60; 95% CI, -1.89 to -1.31; P < 0.00001). In 950 patients from 13 trials, pain at 4 to 6 h favored dextromethorphan (MD, -0.89; 95% CI, -1.11 to -0.66; P < 0.00001). In 797 patients from 12 trials, pain at 24 h favored dextromethorphan (MD, -0.92; 95% CI, -1.24 to -0.60; P < 0.00001). CONCLUSION: This meta-analysis suggests that dextromethorphan use perioperatively reduces the postoperative opioid consumption at 24 to 48 h and pain scores at 1, 4 to 6, and 24 h.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".