Evaluating the Efficacy and Utility of the Automated Pupillometer in Pain Assessment and Opioid Administration Guidance During the Perioperative Period: A Randomized Controlled Trial

Effective intraoperative and postoperative pain management is critical for patient comfort and recovery, yet traditional methods for assessing pain under general anaesthesia are limited by their subjective nature and reliance on vital signs. Automated pupillometry, which gives the parameters of the pupillary light reflex (PLR) components, offers an objective and quantitative approach to evaluating nociception and pain.

This study aims to evaluate the effectiveness of the automated pupillometry in enhancing early postoperative pain control and to assess its utility in guiding opioid administration during the perioperative period.

A prospective, non-blinded randomized controlled trial will be conducted with 68 patients undergoing laparotomy for gastrointestinal surgery. Participants will be randomly assigned to either an interventional group, where analgesia is guided by automated pupillometry measurements, or a control group receiving standard pain management. Key outcomes include the time to first rescue analgesia, self-reported pain scores, opioid consumption. The automated pupillometry measurements will be taken at key surgical moments, including before induction, pre-incision, and during recovery.

Pain scores and rescue analgesia use will be compared between groups using appropriate statistical tests, and Kaplan-Meier survival curves will analyze time to first rescue analgesia. Regression analyses will explore the relationship between pupillometry readings and postoperative pain.

It is anticipated that the automated pupillometry guided group will experience longer intervals before requiring rescue analgesia and report lower pain scores, suggesting improved pain management and reduced opioid use.

This study could validate automated pupillometry as an innovative tool for optimizing postoperative pain management, potentially improving patient outcomes by enabling more precise and effective analgesia in surgical settings.