Low‐ versus high‐dose intraoperative opioids: A systematic review with meta‐analyses and trial sequential analyses
Bibliographic record
Abstract
Background Opioid‐induced hyperalgesia is a state of nociceptive sensitisation secondary to opioid administration. The objective of this meta‐analysis was to test the hypothesis that high‐dose intraoperative opioids contribute to increased post‐operative pain and hyperalgesia when compared with a low‐dose regimen in patients under general anaesthesia. Methods We followed the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses statement guidelines and rated the certainty of evidence with the Grading of Recommendations, Assessment, Development and Evaluation system. Only trials investigating pain outcomes and comparing two different dosages of the same intraoperative opioid in patients under general anaesthesia were included. The primary outcome was pain score (analogue scale, 0‐10) at 24 post‐operative hours. Secondary outcomes included pain score and cumulative intravenous morphine equivalents (mg) consumed at 2 post‐operative hours, together with mechanical pain threshold (g·mm −2 ). Results Twenty‐seven randomised controlled trials, including 1630 patients, were identified. Pain score at rest at 24 post‐operative hours was increased in the high‐dose group (mean difference [95% CI]: −0.2 [−0.4, −0.1]; trial sequential analysis‐adjusted CI: −0.4, −0.02; low certainty of evidence). Similarly, at 2 post‐operative hours, both pain score (mean difference [95% CI]: −0.4 [−0.6, −0.2]; low certainty of evidence) and cumulative intravenous morphine equivalents consumed (mean difference [95% CI]: −1.6 mg [−2.6, −0.7]; low certainty of evidence) were significantly higher in the high‐dose group. Finally, the threshold for mechanical pain was significantly lower in the high‐dose group (mean difference to pressure [95% CI]: 3.8 g·mm −2 [1.8, 5.8]; low certainty of evidence). Conclusions There is low certainty of evidence that high‐dose intraoperative opioid administration increases pain scores in the post‐operative period, when compared with a low‐dose regimen.
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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 | 0.030 | 0.065 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.056 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".