Methods and Timing of the Assessment of Post-Operative Pain in Minimally Invasive Hernia Surgery: A Scoping Review Comparing Robotic With Laparoscopic Repair.

BACKGROUND

Minimally invasive techniques, including laparoscopic and robotic-assisted surgeries, have revolutionized hernia repair by reducing recovery times and postoperative pain (1). Existing studies have explored general outcomes of robotic surgery, including shorter hospital stays and fewer complications (2). However, assessing and comparing postoperative pain in this context remains challenging due to inconsistencies in measurement methods, timing, and reporting practices across studies.

METHODS

A scoping review was conducted on studies published from January 2014 to August 2024. Studies included were those comparing pain outcomes in laparoscopic and robotic-assisted hernia repair. Two independent reviewers performed data extraction, capturing study design, population characteristics, surgical technique, and details on pain assessment methods and timing.

RESULTS

Fifteen of the 403 studies screened were included, comprising 2 randomised controlled trials and 13 cohort studies covering a total of 21 500 patients who underwent either robotic or laparoscopic abdominal wall hernia repairs. Pain assessment methods varied across the studies; the most employed being visual analogue scales (VAS), numerical rating scale (NRS), and opioid analgesic equivalence requirements. Timing of assessments ranged from immediate postoperative periods to 1-year post-surgery. Robotic-assisted surgery was associated with reduced pain scores and analgesic requirements in close to 50% of studies compared to laparoscopic approaches. However, methodological inconsistencies in pain assessment and timing limit the reliability of these findings.

CONCLUSION

This review highlights substantial variability in pain assessment practices in minimally invasive hernia surgery. Robotic-assisted surgery shows promise in reducing postoperative pain, but standardised guidelines for pain measurement are needed to enable more robust comparisons.