Use of Intra-Operative EEG Monitoring for Nociception Balance Quantification—A Narrative Review

<b>Introduction</b>: Balancing hypnosis and antinociception during general anesthesia remains challenging, as traditional clinical and hemodynamic signs incompletely reflect cortical and nociceptive processing. Electroencephalogram (EEG)-derived indices such as qCON (hypnosis) and qNOX (nociception probability) (Quantium Medical, Barcelona, Spain), as well as their predecessors IoC1 (Index of consciousness) and IoC2 (Angel-6000 A multi-parameter Anesthesia Monitor, Shenzen Weihao Kang Medical Technology Co., Ltd., Shenzen, Guangdong, China), have been developed to provide a dual assessment of anesthetic state. Their clinical role, technical limitations, and impact on drug titration, however, remain incompletely defined. <b>Methods</b>: A structured narrative review was conducted based on studies investigating IoC/qCON and qNOX in the context of anesthetic depth or nociception monitoring. Studies were grouped into three thematic domains: (1) validation against clinical or EEG standards, (2) use in guiding anesthetic or opioid administration, and (3) technical characteristics, including signal delay and pharmacodynamic modeling implications. <b>Results</b>: Sixteen studies met inclusion criteria. Eight validation studies demonstrated that IoC/qCON correlates strongly with clinical sedation scales and established EEG-derived indices such as BIS and entropy. Five interventional studies evaluating drug titration found limited impact of qCON-guided hypnosis control on anesthetic consumption but more consistent effects of qNOX/IoC2 guidance on opioid dosing and intraoperative stability. Three technical investigations showed that qCON exhibits processing delays on the order of tens of seconds that can be accounted for by incorporating monitor lag into pharmacodynamic analyses. <b>Conclusions</b>: qCON and qNOX provide complementary EEG-based indices of hypnosis and cortical nociceptive responsiveness. Evidence supports their validity as indicators of anesthetic brain state but highlights technical limitations, such as processing delay and susceptibility to physiologic factors. Their optimal clinical use lies in multimodal monitoring strategies that integrate EEG besides classic clinical and monitoring parameters.