Preoperative Beta Connectivity Predicts Delirium Risk in Older Surgical Patients

The Search for Objective Biomarkers in Postoperative Delirium

Postoperative delirium remains a frequent and dangerous complication for older adults undergoing major surgery, often serving as a harbinger for long-term cognitive dysfunction [1, 2]. While the acute phase is characterized by obvious clinical fluctuations in attention and awareness, the underlying neurobiological vulnerability that predisposes certain patients to these episodes remains difficult to quantify [3, 4]. Recent meta-analytic evidence involving 4,367 patients indicates that intraoperative electroencephalography (EEG) monitoring to avoid excessive anesthetic depth can reduce the incidence of postoperative cognitive complications by 22% (pooled odds ratio 0.78; 95% confidence interval 0.69 to 0.90; P < 0.001) [1, 5]. However, clinicians still lack reliable, objective tools to identify at-risk patients before they reach the operating room or to track neurophysiological recovery after discharge [6, 7]. A multicenter study now examines whether quantitative analysis of brain network connectivity, a statistical method that maps the functional communication and synchronization between distinct brain regions, can identify these hidden vulnerabilities and determine if the delirious brain truly recovers its baseline function [4].

Mapping Cortical Connectivity in the Aging Surgical Population

The researchers conducted a prospective, multicenter cohort study to investigate the neurophysiological markers of delirium in an aging population, enrolling 379 surgical patients aged 65 years or older scheduled for major elective surgery. To ensure that the results specifically reflected surgical vulnerability rather than baseline neurodegeneration, the authors excluded individuals with preexistent cognitive dysfunction. Following data collection, 330 surgical patients retained sufficient EEG data quality for the final analysis. To establish a baseline for comparison, the study also included 57 nonsurgical controls who served as a reference group, allowing the team to distinguish between age-related changes and those specifically associated with the surgical process. The investigation utilized several quantitative EEG measures to assess brain function before surgery and at a three-month follow-up. These metrics included relative power, which measures the proportion of total signal strength within specific frequency bands, and functional connectivity, defined as the statistical correlation between signals from different brain regions. The researchers evaluated functional connectivity through both phase-based methods, which look at the timing of signal peaks, and amplitude-based methods, which look at the correlation of signal strength, to map how distinct cortical areas communicate. Additionally, the analysis incorporated spectral variability (a measure of how much the frequency spectrum fluctuates over time) and signal complexity (a metric of the unpredictability or information content of brain activity). By comparing these parameters across the 330 surgical patients and 57 nonsurgical controls, the study sought to identify whether specific preoperative brain states could predict the onset of postoperative delirium.

Beta-Band Deficits as a Preoperative Risk Signature

The incidence of delirium within the study cohort highlights the prevalence of this complication in the aging surgical population, as 59 individuals (18%) developed postoperative delirium among the 330 surgical patients with evaluable data. When the researchers analyzed the preoperative electroencephalogram recordings, they identified a specific neurophysiological signature that distinguished these patients from those who remained cognitively stable. Specifically, patients who later developed postoperative delirium exhibited significantly lower beta amplitude-based connectivity at baseline (β = -0.36; Pcorrected = 0.04). This measure, which quantifies the degree to which the strength of high-frequency brain waves (13 to 30 Hz) fluctuates in synchronization across different cortical regions, suggests a pre-existing deficit in the coordination of large-scale neural networks. The researchers noted that this finding was highly specific to the beta-band amplitude correlations, as no other electroencephalogram measures, including relative power, phase-based connectivity, spectral variability, or signal complexity, showed significant differences between groups at baseline. This isolation of a single predictive marker suggests that reduced preoperative beta amplitude-based connectivity may serve as a specific marker of neurophysiological vulnerability for postoperative delirium. For the clinician, these data indicate that the risk of delirium may not be a purely acute phenomenon triggered by surgical stress, but rather a manifestation of a pre-existing lack of neural network robustness. Identifying these patients before they reach the operating room could eventually allow for targeted perioperative interventions or more intensive monitoring in those with this specific electrophysiological profile.

Postoperative Recovery and Long-Term Neurophysiological Stability

Longitudinal assessment of these patients provides a critical window into the brain's ability to recover from the metabolic and inflammatory stress of surgery. While postoperative delirium shows electroencephalographic changes during the acute phase, such as slowed rhythms and reduced complexity, the persistence of these neurophysiological disruptions has remained a subject of clinical debate. To investigate the long-term impact of surgical intervention and delirium on brain function, the researchers obtained EEG recordings before surgery and 3 months after surgery. The study utilized linear mixed models (statistical frameworks designed to account for both fixed effects and individual variations over time) to assess the effects of time, surgery, and postoperative delirium on various EEG measures. The longitudinal analysis revealed a notable return to baseline function for the study participants, as three months after surgery, no persistent changes in quantitative EEG characteristics were observed in relation to postoperative delirium occurrence. This finding suggests that the acute neurophysiological instability characterizing the delirious state does not necessarily result in permanent alterations to resting-state brain networks. Furthermore, three months after surgery, no persistent changes in quantitative EEG characteristics were observed in relation to surgery alone, indicating that major elective surgery does not inherently degrade global electrophysiological signatures in patients without pre-existing cognitive impairment. For the practicing clinician, these results provide a nuanced perspective on the brain's resilience following a perioperative insult. The authors suggest that resting-state EEG networks may functionally recover or compensate in this cohort at 3 months postoperative, pointing toward a capacity for neural reorganization or the resolution of transient stressors. While the initial vulnerability is marked by reduced beta connectivity, the absence of long-term quantitative EEG changes suggests that the physiological architecture of the brain may stabilize once the acute phase of recovery is complete.

References

1. Yin Q, Chen D, Gu C. Effect of intraoperative Electroencephalogram-guided anesthesia on postoperative cognitive function in elderly patients: a systematic review, meta-analysis, and trial sequential analysis of randomized controlled trials. BMC Anesthesiology. 2025. doi:10.1186/s12871-025-03297-3

2. Aldecoa C, Bettelli G, Bilotta F, et al. Update of the European Society of Anaesthesiology and Intensive Care Medicine evidence-based and consensus-based guideline on postoperative delirium in adult patients. European Journal of Anaesthesiology. 2023. doi:10.1097/eja.0000000000001876

3. Bowman EML, Sweeney A, McAuley DF, et al. Assessment and report of individual symptoms in studies of delirium in postoperative populations: a systematic review. Age and Ageing. 2024. doi:10.1093/ageing/afae077

4. Montfort SJV, Dellen EV, Stam CJ, et al. Brain network disintegration as a final common pathway for delirium: a systematic review and qualitative meta-analysis. NeuroImage Clinical. 2019. doi:10.1016/j.nicl.2019.101809

5. Xu N, Li L, Wang T, et al. Processed Multiparameter Electroencephalogram-Guided General Anesthesia Management Can Reduce Postoperative Delirium Following Carotid Endarterectomy: A Randomized Clinical Trial. Frontiers in Neurology. 2021. doi:10.3389/fneur.2021.666814

6. Fraiture EJD, Schuijt HJ, Menninga M, et al. Automated EEG-Based Brainwave Analysis for the Detection of Postoperative Delirium Does Not Result in a Shorter Length of Stay in Geriatric Hip Fracture Patients: A Multicentre Randomized Controlled Trial. Journal of Clinical Medicine. 2024. doi:10.3390/jcm13226987

7. Wildes TS, Winter A, Maybrier H, et al. Protocol for the Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES) study: a pragmatic, randomised clinical trial. BMJ Open. 2016. doi:10.1136/bmjopen-2016-011505