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

  • Author: Doleman B, Mathiesen O, Sutton AJ, Cooper NJ, Lund JN, Williams JP

  • Published: Br. J. Anaesh, june 2023


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.

Systematic review protocol: PROSPERO CRD42021269642.

DOI: 10.1016/j.bja.2023.02.041

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