Decision Support Tools for Adjusting Perioperative Opioid Dosing as Individualised Postoperative Pain Management: A Systematic Review

INTRODUCTION: Despite decades of efforts to optimize procedure-specific pain management, up to 60% of surgical patients still experience moderate to severe pain and opioid-related adverse effects. Current guidelines primarily rely on standardised dosing protocols rather than individual patient characteristics, offering limited support for tailoring opioid therapy to patient-specific needs. This systematic review aimed to identify studies on decision support tools for adjusting perioperative systemic opioid dosing as individualised postoperative pain management and evaluate their effects on postoperative outcomes.

METHODS: We searched EMBASE, MEDLINE and Cochrane Library up to August 2025 for studies including adult surgical patients developing, validating or testing decision support tools (prediction models or nociception monitoring systems). Prediction model studies had to include at least two predictors and target the first 24 postoperative hours. Intervention studies had to report pain, opioid use, or opioid-related adverse events within 24 h. Studies on chronic pain, intraoperative-only agents (e.g., remifentanil), or unpublished literature were excluded. Risk of bias was assessed using the Prediction model Risk of Bias Assessment Tool in prediction model studies and Cochrane Risk of Bias and ROBINS-I tool in intervention studies. We conducted meta-analyses for intervention studies (RCTs only) when outcomes were comparable.

RESULTS: We included 19 studies on decision support tools for perioperative opioid management: seven development and one impact study on personalised prediction models and 11 intervention studies on nociception monitoring systems. All prediction model studies predicted postoperative opioid requirements, had a high risk of bias, limited external validation and poor overall performance (R2 range: 0.100-0.313). None were clinically tested or provided advice on optimal opioid dosing. For intervention trials evaluating nociception monitoring systems, meta-analyses showed no significant effect on pain, opioid use, or opioid-related adverse events within 24 h after surgery. No studies tested risk stratified/individualised opioid treatment.

CONCLUSION: No prediction model study provided concrete guidance for individualising systemic opioid treatment. Nociception monitor-guided opioid doses did not improve acute postoperative pain, opioid use or opioid-related adverse events.

EDITORIAL COMMENT: This systematic review assessed if available tested prediction models for individual guiding of opioid analgesic dosing, including monitors designed to assess nociceptive signal influence on clinical status, were of benefit in clinical practice. Findings, for outcomes analgesic effect, opioid dosing, or adverse events related to opioids, none of the models or systems have been demonstrated to have cliear clinical utility for optimizing opioid dosing.