Predicting Postoperative Delirium Using EEG, Genetics and Neurobiomarkers of Cerebral Injury (POD-01)

Predicting Postoperative Delirium Using Intraoperative EEG Alpha Wave Analysis, APOE Genotyping and NfL as a Biomarker of Cerebral Injury

The overall goal of this research project is to elucidate underlying pathophysiological mechanisms of postoperative delirium (POD) and to specifically validate perioperative predictive factors that will help in indentifying patients at higher risk of developing POD.

  1. The main objective is to evaluate whether intraoperative frontal alpha power in unprocessed electroencephalogram (EEG), under general anesthesia, is associated with the occurrence of POD, and whether specific patterns worrelate with the patient's preoperative cognitive status.
  2. As apolipoprotein E (APOE) polymorphism has been shown to be a risk factor of POD, we will specifically analyze whether patients who are APOEe4 carriers present different intraoperative EEG patterns in terms of anteriorization of the alpha frequency band under general anesthesia, and investigate whether the APOEe4 carriers are at higher risk of POD.
  3. In this research project, we will also analyze the perioperative kinetics of serum neurofilament light chain protein (NfL), a biomarker of neuronal injury. We will specifically analyze whether preoperative, as well as postoperative serum NfL levels are higher in patients presenting POD, compared to those who do not experience POD. This will allow studying whether neuronal damage may be involved in the pathogenesis of POD.

Study Overview

Detailed Description

POD is defined as a "fluctuating disturbance in attention that represents an acute change from baseline, accompanied by disturbed cognition or perception, and not due to a pre-existing neurocognitive disorder or occurring in the context of a severely reduced arousal level". Depending on the type of surgery and the studied population, it can occur in 20 to 45% of the older patients. POD is a burden to the health care providers. Indeed, it is strongly associated with increased morbidity and mortality. The pathophysiology of POD is multifactorial and not yet completely elucidated. The aging brain is more vulnerable to the development of POD. However, more than the chronological age, the patient's overall vulnerability and their preexisting cognitive status are indicators of their ability to cope with these perioperative stressors. Indeed, the patient's cognitive status is a leading cause of POD and models predicting POD show poor accuracy because they do not take into account the patient's preoperative cognitive status. Preoperative neurocognitive assessment could be performed but these tests are time-consuming and subject to various influencing factors. Hence, objective tools are required to distinguish patients with preoperative cognitive impairment.

First hypothesis: The presence of a specific intraoperative EEG signal pattern may provide a tool for such identification of patients with underlying preoperative cognitive frailty. Commonly used anesthestic agents for induction and maintaining general anesthesia (e.g. sevoflurane or propofol) provide a typical electroencephalographic pattern with slow/delta and alpha oscillations, predominantly in the frontal cerebral cortex. More specifically, alpha oscillations actually originate from parieto-occipital sites in awake patients and migrate towards frontal regions after the induction of anesthesia. This phenomenon is called the "anteriorization" of the alpha frequency band. Besides, amongst all EEG frequencies, the contribution of alpha oscillations to the global tracing evolve throughout adulthood : the alpha power tends to decrease with age, and this decrease is more pronounced in the presence of underlying cognitive disorder (e.g. mild cognitive impairment, Alzheimer's disease). More importantly, it has been demonstrated that a lower frontal alpha band anteriorization during general anesthesia is associated with lower preoperative cognitive scores. Moreover, these patients might be at higher risk of intraoperative EEG suppression in case of an overdose of anesthetics or, even often, despite a lower dose of anesthetics. In this regard, the presence and the power of frontal alpha oscillations under general anesthesia may be indicators of the patient's preoperative cognitive status and may therefore predict the risk of developing POD.

Second hypothesis: Genetic studies have demonstrated a correlation between specific genotypes and the risk of cognitive decline. APOEe4 genotype is a known risk factor for Alzheimer's disease (AD), and has been shown to be also a risk factor of POD. However, APOEe4 allele is neither necessary nor exclusive to develop AD, and this may also hold true for POD, as this late hypothesis has been rejected in other previous studies. Otherwise, few studies have looked at some EEG particularities according to APOEe4 genotyping, in AD patients and control subjects. Unfortunately, their results regarding the presence of the e4 allele and associated EEG abnormalities are conflicting. To date, no study has related APOE genotyping and intraoperative EEG patterns under general anesthesia.

Third hypothesis: In addition to perioperative episodes of cerebral hypoxia and/or hypoperfusion and neuroinflammation, pathophysiological mechanisms of POD also include a potential direct insult to the brain, induced by both anesthesia and surgery. Yet, the ideal biomarker, highly sensitive for brain injury, as well as highly specific for neuronal tissue remains to be identified. Indeed, the release of such proteins after a neuronal injury can ensue from many levels and some of them have extracranial sources. These sources may therefore influence the observed results. As a conseuquence, in clinical practice, none of the currently evaluated neurobiomarkers (e.g. interleukins, Neuron Specific Enolase, S100 calcium-binding protein B) has emerged as a reliable diagnostic and/or prognostic tool for assessing postoperative neurological complications. Recently, much focus has been given to neurofilaments, as this group of proteins is part of the scaffolding of axons and is exclusively expressed in neuronal tissue. As a consequence, abnormally high levels of neurofilaments in extracellular fluids, such as cerebrospinal fluids (CSF) or serum, correspond specifically to neuronal cell damage, which represents a significant advantage compared to other biomarkers previously tested. Among the three subunits of neurofilament, neurofilament light (NfL) subunit has been shown to be promising. High levels of NfL have been found in a large range of neurodegenerative disorders, but also in acute events such as traumatic brain injury and stroke. Since it has been possible to measure NfL in serum, obviating the need for cerebrospinal fluid samples, their analysis in the perioperative period has been facilitated. Indeed, serum NfL levels have been recently investigated in the perioperative period in various surgical patient populations. These studies provide us information about the kinetics of perioperative NfL release but they show conflicting results regarding a potential correlation between high perioperative NfL levels and the occurrence of POD.

Study Type

Interventional

Enrollment (Actual)

220

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

      • Brussels, Belgium, 1200
        • Cliniques Universitaires Saint-Luc

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

Inclusion Criteria:

  • patients who undergo elective cardiac surgery with cardiopulmonary bypass

Exclusion Criteria:

  • non-French speaking patients
  • hypothermic cardiopulmonary bypass
  • second (or more) cardiac intervention
  • endocarditis
  • preoperative delirium
  • psychiatric disorders
  • uncompleted preoperative neurocognitive tests
  • preoperative anti-epileptic treatment
  • chronic ethylism
  • terminal kidney insufficiency with dialyses

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: EEG for cardiac surgery patients
Patients who undergo elective cardiac surgery with cardiopulmonary bypass, from 18 to >75 years old.
EEG samples will be recorded before and during the cardiac surgery in order to perform spectral and coherence analyses
APOE genotyping will be performed for each patient
5 perioperative blood samples will be taken to measure the evolution of NfL in the serum (before and until postoperative day 5)
Each patient will benefit from a complete neurocognitive evaluation before surgery (battery of validated cognitive tests)

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Postoperative delirium (POD)
Time Frame: from postoperative awakening in ICU until discharge from the hospital (assessed up to 7 days postoperatively)
Development of POD after cardiac surgery (using CAM, CAM-ICU, flow chart review)
from postoperative awakening in ICU until discharge from the hospital (assessed up to 7 days postoperatively)

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Length of stay
Time Frame: Up to one month
Length of stay in the Intensive Care Unit and in hospital
Up to one month
Postoperative cognitive dysfunction
Time Frame: 6 months after surgery
Brief cognitive evaluation by phone (TICS)
6 months after surgery

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Mona Momeni, MD, PhD, Cliniques universitaires Saint-Luc, UCL

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

May 15, 2019

Primary Completion (Actual)

December 15, 2021

Study Completion (Actual)

June 15, 2022

Study Registration Dates

First Submitted

October 11, 2018

First Submitted That Met QC Criteria

October 15, 2018

First Posted (Actual)

October 16, 2018

Study Record Updates

Last Update Posted (Actual)

July 11, 2022

Last Update Submitted That Met QC Criteria

July 8, 2022

Last Verified

July 1, 2022

More Information

Terms related to this study

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

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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