Electroencephalogram Predicts Post-operative Delirium (EPOD)

Frontal-temporal EEG During Anesthesia Recovery Predicts Postoperative Delirium in Neurosurgery: a Single-center, Prospective, Observational Study

The goal of this observational study is to investigate the predictive value of sub-hairline electroencephalography (EEG) during anesthesia recovery for postoperative delirium (POD). The main question to be answered is:

• Can sub-hairline EEG measured during anesthesia recovery serve as a reliable predictor of POD? Adult patients undergoing elective craniotomy and admitted to the ICU will be enrolled. Sub-hairline EEG will be monitored until ICU discharge.

Study Overview

• Status: Recruiting
• Conditions: Neurosurgery; Brain Tumor Adult; Delirium - Postoperative
• Intervention / Treatment: Diagnostic test: Sub-hairline EEG Monitoring

Detailed Description

Postoperative delirium (POD) is common neurological complication following major surgery, particularly in neurosurgical patients with the incidence ranges from 5% to 37%, depending on the diagnostic criteria and patient subgroups. POD has been associated with increased morbidity, prolonged hospitalisation, long-term cognitive impairment, and higher healthcare costs. Despite its clinical significance, early identification of patients at risk for POD remains a challenge. Electroencephalography (EEG) has been extensively utilised for monitoring brain function in anaesthesia and critical care settings. However, the feasibility and predictive value of sub-hairline EEG during anaesthesia recovery for POD remain largely unexplored.

This prospective observational study aims to assess whether sub-hairline EEG parameters recorded during the immediate anaesthesia recovery phase can serve as reliable predictors of POD in adult patients undergoing elective craniotomy. The study will include patients scheduled for elective craniotomy who are admitted to the intensive care unit (ICU) postoperatively.

Study Design and Procedures

Sub-hairline EEG monitoring will commence at the end of surgery and continue throughout the early recovery phase in the ICU. EEG signals will be continuously recorded using a standardized EEG montage, focusing on frontal and temporal regions. The EEG-derived parameters of interest include:

• Spectral power across different frequency bands (delta, theta, alpha, beta)
• Burst suppression ratio
• Functional connectivity metrics (coherence, phase-amplitude coupling) POD will be assessed using validated screening tools, including the Confusion Assessment Method for the ICU (CAM-ICU), the Delirium Observation Screening Scale (DOSS), and the Fluctuating Mental Status Evaluation (FMSE) within seven days postoperatively. Assessments will be conducted after extubation and between 10:00 AM and 4:00 PM within the first seven postoperative days. A total of four visits will be performed: on postoperative day 1, postoperative day 7, and two randomly selected days between postoperative days 2 and 5.

Data Collection and Quality Assurance

To ensure data quality and integrity, the study will implement the following procedures:

• Standardized EEG Acquisition and Processing: EEG signals will be collected using a predefined protocol with strict artifact rejection criteria.
• Clinical Data Recording: Patient demographics, perioperative anesthetic management, hemodynamic stability, postoperative analgesia, respiratory function, and ECG parameters will be recorded to assess potential confounding factors.
• Source Data Verification: EEG recordings and clinical data will be cross-checked with electronic medical records for accuracy and completeness.
• Quality Control Measures: Data entry will undergo automated range and consistency checks to minimize errors. Missing or inconsistent data will be flagged and reviewed.

Sample Size and Statistical Analysis Plan A sample size calculation will be conducted to ensure adequate power to detect significant associations between EEG parameters and POD incidence. Based on our past studies, the incidence of POD is 30% after neurosurgery in our hospital. According to the literature search results and related studies, the area under the curve was 0.73, the two-sided test error was 0.05, the statistical power was 0.9, and the 10% dropout rate was considered. Eventually, we plan to enroll 137 participants for elective neurosurgery.

Primary Analysis:

• The association between EEG parameters during anesthesia recovery and POD will be evaluated using multivariable logistic regression, adjusting for potential confounders.
• Time-series EEG changes will be analyzed using repeated-measures ANOVA to track EEG dynamics over time.

Secondary Analysis:

• EEG biomarkers predictive of POD severity will be identified using machine learning approaches, such as decision trees and support vector machines.
• Subgroup analysis will assess differences based on age, baseline cognitive function, and surgical duration.

Expected Impact By leveraging non-invasive sub-hairline EEG monitoring, this study aims to provide insights into the neurophysiological mechanisms underlying POD and identify early EEG biomarkers for risk stratification. If successful, this research could contribute to the development of real-time EEG-based monitoring tools for early POD detection and prevention, ultimately improving postoperative outcomes in neurosurgical patients.

• Study Type: Observational
• Enrollment (Estimated): 137

Contacts and Locations

• Study Contact: Name: Zhonghua Shi, PhD,MD; Phone Number: 010-62856764; Email: z.shi@mail.ccmu.edu.cn
• Study Contact Backup: Name: Liuhan Wu; Phone Number: 010-62856764; Email: wlh920585@163.com

Study Locations

• China
  • Beijing
    • Beijing, Beijing, China, 100090
      • Recruiting
      • Beijing Sanbo Brain Hospital, Capital Medical University
      • Contact: Zhonghua Shi, PhD,MD; Phone Number: 010-62856764; Email: z.shi@mail.ccmu.edu.cn
    • Beijing, Beijing, China, 100093
      • Recruiting
      • Sanbo Brain Hospital, Captial Medical Universtiy
      • Contact: Zhonghua Shi, MD, PhD; Phone Number: +86-010-62856765; Email: z.shi@mail.ccmu.edu.cn

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

The study will recruit participants from patients scheduled for elective neurosurgical procedures at Sanbo Brain Hospital, Capital Medical Universtiy in Beijing, China. The population will consist of adult patients aged ≥18 years who are classified as ASA physical status I-II, indicating generally healthy individuals or those with mild systemic disease. Participants will be identified through pre-surgical assessments and referred by their attending neurosurgeons for enrollment in the study. This cohort will be selected from those undergoing elective craniotomy. Eligible participants will be consented prior to surgery, and sub-hairline EEG monitoring will be initiated during the early anesthesia recovery phase in the ICU.

Description

Inclusion Criteria:

• Age ≥ 18 years
• Planned elective neurosurgical surgery
• ASA physical status I-II
• Signed informed consent

Exclusion Criteria:

• Known neurological or psychiatric disorders (e.g., epilepsy, Parkinson's disease)
• Preoperative cognitive impairment (MMSE score < 24)
• Long-term use of central nervous system drugs (e.g., antidepressants, antipsychotics)
• Language barriers
• History of craniotomy within the last 12 months
• Inability to place frontal-temporal electrodes due to conditions such as frontal skin injury, severe agitation, or a coronal incision for surgery
• Pregnant or breastfeeding women

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
POD group; Patients who develop POD within seven days after surgery, as assessed using validated screening tools (CAM-ICU, DOSS, FMSE)	Diagnostic test: Sub-hairline EEG Monitoring; Participants will receive standard postoperative care as per institutional protocols, including neuromonitoring, delirium screening, and ICU management. The study will not alter or assign any treatments but will analyze the association between sub-hairline EEG parameters and postoperative delirium (POD) outcomes; Other Names: Delirium Assessment; Clinical Data Collection
Non-POD group; Patients who do not develop POD within the seven-day postoperative period.	Diagnostic test: Sub-hairline EEG Monitoring; Participants will receive standard postoperative care as per institutional protocols, including neuromonitoring, delirium screening, and ICU management. The study will not alter or assign any treatments but will analyze the association between sub-hairline EEG parameters and postoperative delirium (POD) outcomes; Other Names: Delirium Assessment; Clinical Data Collection

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Incidence of Postoperative Delirium (POD)	The primary outcome of this study is to assess whether sub-hairline EEG parameters recorded during anesthesia recovery can reliably predict the incidence of postoperative delirium (POD) within the first 7 days following elective craniotomy.	Within 7 days post-surgery

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Spectral power of Sub-Hairline EEG theta wave	To evaluate whether changes in sub-hairline EEG parameters (e.g., spectral power, burst suppression ratio, and connectivity metrics) during the early postoperative period are associated with the onset and severity of POD.	Within 7 days post-surgery
Hospital Length of Stay	To investigate if the use of sub-hairline EEG during anesthesia recovery correlates with the length of ICU and total hospital stay.	through study completion, an average of 30 days
Incidence of Postoperative Complications (PPCs)	To evaluate the incidence of postoperative complications, including pneumonia, atelectasis, brain ischemia, edema, and haemorrhage, and whether these are correlated with sub-hairline EEG parameters.	through study completion, an average of 1 week
Analysis of EEG Patterns and Delirium Onset	To explore any correlation between specific sub-hairline EEG patterns (e.g., burst suppression ratio, alpha or theta waves) and the early onset of delirium.	through study completion, an average of 1 week
Phase-Locking Value between sub-Hairline EEG oscillations and respiratory rhythm	This secondary outcome measure aims to investigate the correlation between sub-hairline EEG parameters and other physiological signals, including electrocardiogram (ECG) and respiratory parameters, to determine their potential predictive value for POD. This study will explore whether these signals show significant interactions or patterns that could help predict the onset of POD and its severity.	through study completion, an average of 1 week

Collaborators and Investigators

• Sponsor: Beijing Sanbo Brain Hospital
• Investigators: Principal Investigator: Zhonghua Shi, PhD,MD, Capital Medical University

Study record dates

Study Major Dates

• Study Start (Actual): March 1, 2025
• Primary Completion (Estimated): March 1, 2026
• Study Completion (Estimated): May 1, 2026

Study Registration Dates

• First Submitted: March 12, 2025
• First Submitted That Met QC Criteria: March 18, 2025
• First Posted (Actual): March 25, 2025

Study Record Updates

• Last Update Posted (Actual): March 25, 2025
• Last Update Submitted That Met QC Criteria: March 18, 2025
• Last Verified: February 1, 2025

More Information

Terms related to this study

• Keywords: Postoperative delirium; electroencephalography; neurosurgical patients; Sub-hairline EEG; Confusion Assessment Method for ICU (CAM-ICU); Delirium Observation Screening Scale (DOSS); Fluctuating Mental Status Evaluation (FMSE)
• Additional Relevant MeSH Terms: Neurologic Manifestations; Nervous System Diseases; Mental Disorders; Confusion; Neurobehavioral Manifestations; Neurocognitive Disorders; Delirium
• Other Study ID Numbers: -BeijingSBH; SB- (Other Identifier: Beijing Sanbo Brain Hospital)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No