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NCT Number: NCT05992506

Electroencephalographic Biomarker to Predict Postoperative Delirium

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.

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Key information

Age range

60 year–100 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Hospital Clinico Universidad de Chile, Santiago, Santiago Metropolitan, Chile

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About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

POD risk estimation using PEUMA

Diagnostic Test

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

Primary outcomes

  1. Postoperative Delirium

    Time frame: First 3 days after surgery

    Incidence of POD in the cohort diagnosed using the Confusion Assessment Method (CAM) twice/day

Secondary outcomes

  1. Death

    Time frame: 30 days after surgery

    Number of deceased patients

  2. Delirium Severity

    Time frame: First 3 days after surgery

    Delirium severity assessed by Cognitive Assessment Method - Severity (CAM-S)

  3. Delirium Duration

    Time frame: First 3 days after surgery

    Duration of delirium during the postoperative period

  4. Need for Mechanical Ventilation

    Time frame: First 3 days after surgery

    Number of patients that needed mechanical ventilation

  5. Reintervention

    Time frame: First 3 days after surgery

    Number of patients who required other unanticipated surgery after the primary intervention

  6. Unanticipated ICU hospitalization

    Time frame: First 3 days after surgery

    Number of patients that needed unanticipated intensive care unit (ICU) care

Sponsors and collaborators

Lead sponsor

University of Chile

Other

Collaborators

  • Clinica Santa Maria
  • Hospital Base San Jose Osorno
  • Instituto Nacional del Cancer, Chile
  • Pontificia Universidad Catolica de Chile

Registry information

Official study title

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

Important dates

Study start
2023
Primary completion
2025
Study completion
2026
First posted
Aug 15, 2023
Registry last updated
Nov 20, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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