ReviewJournal of anesthesia and translational medicine2026
Electroencephalographic phenotypes of postoperative delirium in the perioperative period.
Review in Journal of anesthesia and translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Long-Term Cognitive and Functional Outcomes of Anesthesia and Surgery in Patients with Dementia.Healthcare (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Postoperative delirium (POD) is a common and severe complication among older surgical patients. Perioperative electroencephalography (EEG) monitoring provides a noninvasive, real-time window into cerebral neural activity. Traditionally, EEG has been simplified into single indices, such as the bispectral index (BIS), to guide anesthetic depth titration. However, recent large-scale clinical trials have demonstrated that avoiding EEG suppression based solely on such indices does not reduce the incidence of POD. This discrepancy partly arises because conventional indices are primarily derived from frontal EEG signals and fail to fully exploit the multidimensional information distributed across the whole brain. This review highlights that high-dimensional features embedded in raw EEG-including spectral characteristics, oscillatory dynamics, brain network connectivity, and aperiodic components-serve as key biomarkers for identifying individual neural vulnerability and POD risk. We systematically summarize spatiotemporal EEG phenotypes associated with POD pathophysiology, encompassing age-related baseline features, intraoperative high-risk patterns (such as burst suppression), and abnormal emergence trajectories indicative of failed brain network reorganization. Accumulating evidence indicates that aberrations in these EEG features are closely associated with POD occurrence and adverse clinical outcomes. Therefore, future EEG interpretation must move beyond single "depth" indices toward a mechanism-driven assessment that integrates high-dimensional EEG features with individual baseline characteristics, thereby providing novel strategies for the precise prevention of POD.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.