Pharmacological agents for prevention of pruritus in women undergoing Caesarean delivery with neuraxial morphine: a systematic review and Bayesian network meta-analysis
Bibliographic record
Abstract
BACKGROUND: Neuraxial opioids provide effective analgesia for Caesarean delivery, however, pruritus can be a troubling side-effect. Effective agents to prevent pruritus are needed. Our objective was to perform an updated systematic review and network meta-analysis to provide clinicians with a comparison of relative efficacy of available interventions to reduce the incidence of pruritus, induced by either intrathecal or epidural single-shot morphine, in women undergoing Caesarean delivery. METHODS: Databases systematically searched (up to January 2022) included PubMed MEDLINE, Web of Science, EBSCO CINAHL, Embase, LILACS, and two Cochrane databases. We included randomised, controlled trials involving adult female patients undergoing Caesarean delivery. We pooled trials comparing interventions used for preventing pruritus after Caesarean delivery and performed a Bayesian model network meta-analysis. RESULTS: The final primary network included data from comparisons of 14 distinct interventions (including placebo) used to reduce the incidence of pruritus in 6185 participants. We judged five interventions to be 'definitely superior' to placebo: propofol, opioid agonist-antagonists (neuraxial), opioid antagonists, opioid agonist-antagonists (systemic), and serotonin antagonists. For the network evaluating the incidence of severe pruritus (warranting additional therapeutic treatment of pruritus), data were available for 14 interventions (including placebo) in 4489 patients. For this outcome, we judged three interventions to be 'definitely superior' to placebo: dopamine antagonists (neuraxial) and systemic and neuraxial opioid agonist-antagonists. CONCLUSION: Our analysis found several interventions to be effective in reducing the incidence of pruritus. Although sub-hypnotic doses of propofol appear to have an antipruritic effect, replication of this finding and further investigation of optimal dosing are warranted. SYSTEMATIC REVIEW PROTOCOL: PROSPERO (CRD42022367058).
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.023 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".