Quality of meta-analyses of non-opioid, pharmacological, perioperative interventions for chronic postsurgical pain: a systematic review

Background In an attempt to aggregate observations from clinical trials, several meta-analyses have been published examining the effectiveness of systemic, non-opioid, pharmacological interventions to reduce the incidence of chronic postsurgical pain. Objective To inform the design and reporting of future studies, the purpose of our study was to examine the quality of these meta-analyses. Evidence review We conducted an electronic literature search in Embase, MEDLINE, and the Cochrane Database of Systematic Reviews. Published meta-analyses, from the years 2010 to 2020, examining the effect of perioperative, systemic, non-opioid pharmacological treatments on the incidence of chronic postsurgical pain in adult patients were identified. Data extraction focused on methodological details. Meta-analysis quality was assessed using the A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2) critical appraisal tool. Findings Our search yielded 17 published studies conducting 58 meta-analyses for gabapentinoids (gabapentin and pregabalin), ketamine, lidocaine, non-steroidal anti-inflammatory drugs, and mexiletine. According to AMSTAR 2, 88.2% of studies (or 15/17) were low or critically low in quality. The most common critical element missing was an analysis of publication bias. Trends indicated an improvement in quality over time and association with journal impact factor. Conclusions With few individual trials adequately powered to detect treatment effects, meta-analyses play a crucial role in informing the perioperative management of chronic postsurgical pain. In light of this inherent value and despite a number of attempts, high-quality meta-analyses are still needed.

Automated summary

This study examined the quality of meta-analyses on non-opioid pharmacological interventions for chronic postsurgical pain and found that the majority of them were of low quality, lacking analysis of publication bias. Quality improved over time and was associated with journal impact factor.