Electroencephalographic Biomarker to Predict Postoperative Delirium

NCT ID: NCT05992506

Last Updated: 2025-11-20

Basic Information

• Recruitment Status: ACTIVE_NOT_RECRUITING
• Total Enrollment: 264 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2023-09-01
• Study Completion Date: 2026-06-30

Brief Summary

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.

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.

Conditions

Postoperative Delirium

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

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.

POD risk estimation using PEUMA

Intervention Type: DIAGNOSTIC_TEST

A software will analyze intraoperative EEG recording for the estimation of a POD Risk Index

Interventions

POD risk estimation using PEUMA

A software will analyze intraoperative EEG recording for the estimation of a POD Risk Index

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

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

• Minimum Eligible Age: 60 Years
• Maximum Eligible Age: 100 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Instituto Nacional del Cancer, Chile

UNKNOWN

Sponsor Role: collaborator

Pontificia Universidad Catolica de Chile

OTHER

Sponsor Role: collaborator

Hospital Base San Jose Osorno

UNKNOWN

Sponsor Role: collaborator

Clinica Santa Maria

OTHER

Sponsor Role: collaborator

University of Chile

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

Hospital Clinico Universidad de Chile

Santiago, Santiago Metropolitan, Chile

Instituto Nacional del Cancer

Santiago, Santiago Metropolitan, Chile

Countries

Chile

References

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.

Reference Type: RESULT

PMID: 32188600 (View on PubMed)

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.

Reference Type: RESULT

PMID: 31680886 (View on PubMed)

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.

Reference Type: RESULT

PMID: 35396283 (View on PubMed)

Other Identifiers

IT21I0041

Identifier Type: -

Identifier Source: org_study_id