Journal of Personalized Medicine (Oct 2023)

Pain Assessment Using the Analgesia Nociception Index (ANI) in Patients Undergoing General Anesthesia: A Systematic Review and Meta-Analysis

  • Min Kyoung Kim,
  • Geun Joo Choi,
  • Kyung Seo Oh,
  • Sang Phil Lee,
  • Hyun Kang

DOI
https://doi.org/10.3390/jpm13101461
Journal volume & issue
Vol. 13, no. 10
p. 1461

Abstract

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The analgesia nociception index (ANI) has emerged as a potential measurement for objective pain assessment during general anesthesia. This systematic review and meta-analysis aimed to evaluate the accuracy and effectiveness of ANI in assessing intra- and post-operative pain in patients undergoing general anesthesia. We conducted a comprehensive search of Ovid-MEDLINE, Ovid-EMBASE, Cochrane Central Register of Controlled Trials, Google Scholar, public clinical trial databases (ClinicalTrials and Clinical Research Information Service), and OpenSIGLE to identify relevant studies published prior to May 2023 and included studies that evaluated the accuracy and effectiveness of ANI for intra- or post-operative pain assessment during general anesthesia. Among the 962 studies identified, 30 met the eligibility criteria and were included in the systematic review, and 17 were included in the meta-analysis. For predicting intra-operative pain, pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under curve of ANI were 0.81 (95% confidence interval [CI] = 0.79–0.83; I2 = 68.2%), 0.93 (95% CI = 0.92–0.93; I2 = 99.8%), 2.32 (95% CI = 1.33–3.30; I2 = 61.7%), and 0.77 (95% CI = 0.76–0.78; I2 = 87.4%), respectively. ANI values and changes in intra-operative hemodynamic variables showed statistically significant correlations. For predicting post-operative pain, pooled sensitivity, specificity, and DOR of ANI were 0.90 (95% CI = 0.87–0.93; I2 = 58.7%), 0.51 (95% CI = 0.49–0.52; I2 = 99.9%), and 3.38 (95% CI = 2.87–3.88; I2 = 81.2%), respectively. ANI monitoring in patients undergoing surgery under general anesthesia is a valuable measurement for predicting intra- and post-operative pain. It reduces the use of intra-operative opioids and aids in pain management throughout the perioperative period.

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