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

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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
<p>Background</p> <p>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.</p> <p><br></p> <p>Methods</p> <p>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.</p> <p><br></p> <p>Results</p> <p>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.</p> <p><br></p> <p>Conclusions</p> <p>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.</p>

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

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