Electroencephalographic Biomarker to Predict Postoperative Delirium

Electroencephalographic Biomarker to Predict the Development of Postoperative Delirium: a Protocol of an Observational Study in a Cohort of Patients From Five Centers

Acute post-operatory cognitive dysfunction states are one of the most important complications in older patients that underwent surgery. Among them postoperative delirium (POD) is the the most studied. Patients who develop delirium have poorer long-term outcomes, such as longer length of hospital stay, institutionalization at discharge, and even higher mortality, and consequently, the human and economic costs significantly increase for the health system. Here the research team will use an observational cohort, investigator blinded in five-center with a primary endpoint to validate intraoperative EEG analysis as a reliable biomarker of postoperative delirium.

Study Overview

• Status: Active, not recruiting
• Conditions: Postoperative Delirium
• Intervention / Treatment: Diagnostic test: POD risk estimation using PEUMA

Detailed Description

Acute post-operatory cognitive dysfunction states are one of the most frequent complications in older patients after surgery, being POD the most important. Previous studies have shown than the incidence of POD in older patients range between 10-50%. Patients who develop POD have poorer long-term outcomes, such as longer length of hospital stay, institutionalization at discharge, and even higher mortality. Consequently, the human and economic costs associated to POD represents an important issue for health systems worldwide.

A key element to diminish POD and its burden on healthcare is early diagnostic. Current risk assessment tools are centered on clinical approaches based on cognitive tests (i.e., MoCA) and/or prediction models that uses patients' clinical variables (i.e., DELPHI score). We have developed a strategy that uses intraoperative EEG features as building blocks for a new POD risk assessment predictive model. This system, called PEUMA, uses data obtained from 95 patients from a previous study (NCT04214496).

This will be a multicenter (five-centers), observational study and its primary outcome will be PEUMA's ability to predict POD.

To calculate the sample size, the methodology described by Riley et al was used. This method is specially designed for clinical prediction models. Such a tool is available online (https://mvansmeden.shinyapps.io/BeyondEPV/). The parameters used were the following:

• Number of predictor candidates: 4
• Fraction of events: 0.22. 22% was used because it is the incidence of POD in the analysis of the preliminary data of the first stage and these are in the reporting range common worldwide.
• Estimation error of the classifier: 0.06. The authors suggest prediction errors small when evaluating binary outcomes (Yes POD/No POD) The calculation indicates a sample size of 240 patients. Considering a loss of 10% (in the preliminary results of the first stage the loss was 8%), the sample size is 264 patients.

• Study Type: Observational
• Enrollment (Estimated): 264

Contacts and Locations

Study Locations

• Chile
  • Santiago Metropolitan
    • Santiago, Santiago Metropolitan, Chile, 8380456
      • Hospital Clínico Universidad de Chile
    • Santiago, Santiago Metropolitan, Chile
      • Instituto Nacional del Cancer

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Patients at risk of developing POD will be evaluated in the pre and postoperative period for cognitive dysfunction and the appearance of POD. In the intraoperative period, an EEG-based monitorization will be performed using a SedLine (Masimo, CA) Monitor.

Description

Inclusion Criteria:

• Age ≥ 60 years old
• Scheduled for high-risk elective surgery
• Need for at least 3 days of hospital stay after surgery
• Surgery performed under general anesthesia
• Written informed consent for participation in the trial

Exclusion Criteria:

• Patients with preoperative delirium or dementia
• Patients using neuroleptics drug during the past 6 months
• Patients with a history of encephalopathy, psychosis, stroke or brain trauma with neurologic sequels
• The use of ketamine or dexmedetomidine during surgery
• Emergency surgery
• Mechanical ventilation during the 72 after surgery
• Analphabetism
• Patients who do not talk Spanish
• Patients included in another clinical trial

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Patients at risk of developing POD; Patients older than 60 years; Scheduled for elective surgery of moderate or high risk (defined as that which requires a subsequent hospitalization of at least 3 days) under general anesthesia.; Signed informed consent.	Diagnostic test: POD risk estimation using PEUMA; A software will analyze intraoperative EEG recording for the estimation of a POD Risk Index

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Postoperative Delirium	Incidence of POD in the cohort diagnosed using the Confusion Assessment Method (CAM) twice/day	First 3 days after surgery

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Death	Number of deceased patients	30 days after surgery
Delirium Severity	Delirium severity assessed by Cognitive Assessment Method - Severity (CAM-S)	First 3 days after surgery
Delirium Duration	Duration of delirium during the postoperative period	First 3 days after surgery
Need for Mechanical Ventilation	Number of patients that needed mechanical ventilation	First 3 days after surgery
Reintervention	Number of patients who required other unanticipated surgery after the primary intervention	First 3 days after surgery
Unanticipated ICU hospitalization	Number of patients that needed unanticipated intensive care unit (ICU) care	First 3 days after surgery

Collaborators and Investigators

• Sponsor: University of Chile
• Collaborators: Pontificia Universidad Catolica de Chile; Clinica Santa Maria; Instituto Nacional del Cancer, Chile; Hospital Base San Jose Osorno

Publications and helpful links

General Publications

• Riley RD, Ensor J, Snell KIE, Harrell FE Jr, Martin GP, Reitsma JB, Moons KGM, Collins G, van Smeden M. Calculating the sample size required for developing a clinical prediction model. BMJ. 2020 Mar 18;368:m441. doi: 10.1136/bmj.m441. No abstract available.
• Gutierrez R, Egana JI, Saez I, Reyes F, Briceno C, Venegas M, Lavado I, Penna A. Intraoperative Low Alpha Power in the Electroencephalogram Is Associated With Postoperative Subsyndromal Delirium. Front Syst Neurosci. 2019 Oct 18;13:56. doi: 10.3389/fnsys.2019.00056. eCollection 2019.
• Wong CK, van Munster BC, Hatseras A, Huis In 't Veld E, van Leeuwen BL, de Rooij SE, Pleijhuis RG. Head-to-head comparison of 14 prediction models for postoperative delirium in elderly non-ICU patients: an external validation study. BMJ Open. 2022 Apr 8;12(4):e054023. doi: 10.1136/bmjopen-2021-054023.

Study record dates

Study Major Dates

• Study Start (Actual): September 1, 2023
• Primary Completion (Actual): October 31, 2025
• Study Completion (Estimated): June 30, 2026

Study Registration Dates

• First Submitted: August 7, 2023
• First Submitted That Met QC Criteria: August 7, 2023
• First Posted (Actual): August 15, 2023

Study Record Updates

• Last Update Posted (Actual): November 20, 2025
• Last Update Submitted That Met QC Criteria: November 17, 2025
• Last Verified: October 1, 2025

More Information

Terms related to this study

• Keywords: EEG; Anesthesia; Risk Assessment; Postoperative Delirium
• Additional Relevant MeSH Terms: Neurologic Manifestations; Nervous System Diseases; Mental Disorders; Postoperative Complications; Pathologic Processes; Confusion; Neurobehavioral Manifestations; Neurocognitive Disorders; Delirium; Pathological Conditions, Signs and Symptoms; Signs and Symptoms; Emergence Delirium
• Other Study ID Numbers: IT21I0041

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED
• IPD Plan Description: Individual participant data might be shared with other researchers only if participants give written consent for that.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No