Beyond processed depth targets: frontal EEG patterns, brain vulnerability, and postoperative delirium in older adults

Abstract

Abstract Limited-channel frontal electroencephalography is widely used during anesthesia through processed EEG platforms, but clinical interpretation often remains centered on numerical depth indices. This narrative review examines whether frontal EEG signals, including raw waveforms, suppression behavior, spectral features, and processed index behavior, may provide information beyond hypnotic depth in older adults at risk for postoperative delirium. A targeted literature search was performed in PubMed/MEDLINE and Google Scholar for articles published from database inception through April 30, 2026. Priority was given to randomized trials, systematic reviews, meta-analyses, consensus statements, prospective observational studies, and mechanistic studies relevant to processed EEG monitoring, frontal EEG interpretation, postoperative delirium, aging, frailty, anesthesia, and critical care. Evidence from randomized trials and systematic reviews suggests that processed EEG-guided anesthetic titration and suppression minimization alone do not reliably prevent postoperative delirium. However, several clinically accessible frontal EEG patterns may provide contextual information about anesthetic sensitivity and reduced cerebral reserve. These include reduced frontal alpha power, early or disproportionate burst suppression, spectral slowing or low spectral edge frequency, and disorganized emergence. Their interpretation depends on anesthetic dose and agent, hemodynamics, signal quality, artifact burden, frailty, baseline cognition, and postoperative recovery context. Limited-channel frontal EEG should be interpreted as a contextual brain-monitoring signal rather than a single-number depth target. Future studies should test whether multimodal frameworks integrating frontal EEG patterns with physiologic and patient-level variables improve postoperative neurocognitive outcomes.

The authors' abstract, as published at the source. Journal of Clinical Monitoring and Computing, 2026 · DOI ↗