Effect of nociception level index‐guided intra‐operative analgesia on early postoperative pain and opioid consumption: a systematic review and meta‐analysis
Bibliographic record
Abstract
Acute postoperative pain remains a critical treatment priority and has prompted a search for technologies and techniques to assist with intra-operative analgesic monitoring and management. Anaesthetists traditionally rely on clinical judgement to guide intra-operative analgesia, but several emerging technologies such as the nociception level index herald the possibility of routine intra-operative analgesia monitoring. However, the impact of devices like nociception level index on postoperative outcomes has not been proven. We undertook a systematic review and meta-analysis of articles which compared nociception level index-guided analgesia to standard care. The primary outcomes were pain intensity and opioid consumption during the first 60-120 min after surgery. Secondary outcomes were the incidence of postoperative nausea and vomiting and duration of stay in the post-anaesthesia care unit. Ten studies, collectively including 662 patients and published between 2019 and 2023, met inclusion criteria for both the qualitative systematic review and quantitative meta-analysis. Risk of methodological bias was generally low or unclear, and six studies reported a significant conflict of interest relevant to their findings. Our meta-analysis was performed using a random-effects model. It found statistically significant benefits of nociception level index-guided analgesia for early postoperative pain (mean (95%CI) difference -0.46 (-0.88 to -0.03) on an 11-point scale, p = 0.03), and opioid requirement (mean (95%CI) difference -1.04 (-1.94 to -0.15) mg intravenous morphine equivalent, p = 0.02). Our meta-analysis of the current literature finds that nociception level index-guided analgesia statistically significantly reduces reported postoperative pain intensity and opioid consumption but fails to show clinically relevant outcomes. We found no evidence that nociception level index-guided analgesia affected postoperative nausea and vomiting nor duration of stay in the post-anaesthesia care unit.
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.051 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".