University of Leicester
Browse
1-s2.0-S0007091223001307-main.pdf (676.55 kB)

Non-opioid analgesics for the prevention of chronic postsurgical pain: a systematic review and network meta-analysis.

Download (676.55 kB)
journal contribution
posted on 2023-05-16, 11:45 authored by Brett Doleman, Ole Mathiesen, Alex J Sutton, Nicola J Cooper, Jon N Lund, John P Williams

Background

Chronic postsurgical pain is common after surgery. Identification of non-opioid analgesics with potential for preventing chronic postsurgical pain is important, although trials are often underpowered. Network meta-analysis offers an opportunity to improve power and to identify the most promising therapy for clinical use and future studies.


Methods

We conducted a PRISMA-NMA-compliant systematic review and network meta-analysis of randomised controlled trials of non-opioid analgesics for chronic postsurgical pain. Outcomes included incidence and severity of chronic postsurgical pain, serious adverse events, and chronic opioid use.


Results

We included 132 randomised controlled trials with 23 902 participants. In order of efficacy, i.v. lidocaine (odds ratio [OR] 0.32; 95% credible interval [CrI] 0.17–0.58), ketamine (OR 0.64; 95% CrI 0.44–0.92), gabapentinoids (OR 0.67; 95% CrI 0.47–0.92), and possibly dexmedetomidine (OR 0.36; 95% CrI 0.12–1.00) reduced the incidence of chronic postsurgical pain at ≤6 months. There was little available evidence for chronic postsurgical pain at >6 months, combinations agents, chronic opioid use, and serious adverse events. Variable baseline risk was identified as a potential violation to the network meta-analysis transitivity assumption, so results are reported from a fixed value of this, with analgesics more effective at higher baseline risk. The confidence in these findings was low because of problems with risk of bias and imprecision.


Conclusions

Lidocaine (most effective), ketamine, and gabapentinoids could be effective in reducing chronic postsurgical pain ≤6 months although confidence is low. Moreover, variable baseline risk might violate transitivity in network meta-analysis of analgesics; this recommends use of our methods in future network meta-analyses.

History

Author affiliation

Department of Health Sciences, University of Leicester

Version

  • VoR (Version of Record)

Published in

British journal of anaesthesia

Volume

130

Issue

6

Pagination

719-728

Publisher

Elsevier BV

issn

0007-0912

eissn

1471-6771

Copyright date

2023

Available date

2023-05-16

Spatial coverage

England

Language

eng

Usage metrics

    University of Leicester Publications

    Categories

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC