Clinical Evaluation of Chronic Consciousness Disorders Using Resting-state EEG and ERP

Sponsor
First Affiliated Hospital of Zhejiang University (Other)
Overall Status
Recruiting
CT.gov ID
NCT05949528
Collaborator
(none)
200
1
30.6
6.5

Study Details

Study Description

Brief Summary

Currently, there are significant challenges in the clinical assessment of patients with consciousness disorders, such as distinguishing between vegetative state (VS) and minimally conscious state (MCS), and predicting patient prognosis. This study aims to utilize different research techniques, such as auditory stimulation, as well as modified microstate methods, to enhance the disease classification and prognosis prediction of patients with chronic consciousness disorders.

Condition or Disease Intervention/Treatment Phase
  • Other: no intervention

Detailed Description

The investigators collected resting-state electroencephalograms (EEGs) and EEGs under various event-related potential (ERP) stimuli from patients with chronic consciousness disorders, and performed analyses on these data. The resting-state EEGs were subjected to spectral analysis and microstate analysis. The ERP EEGs were analyzed in the time domain, as well as for phase coupling and other measures.Using these computed indicators, the investigators use machine learning, deep learning, and other methods to predict disease classification and prognosis assessment in patients with chronic consciousness disorders.

Study Design

Study Type:
Observational [Patient Registry]
Anticipated Enrollment :
200 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
Assessing Chronic Consciousness Disorders in Patients Using Clinical Evaluation With Resting-state EEG and ERPs: an Extensive Study Exploring Efficacy and Diagnostic Potential of EEG and ERP Measurements
Actual Study Start Date :
Dec 12, 2021
Anticipated Primary Completion Date :
Dec 30, 2023
Anticipated Study Completion Date :
Jun 30, 2024

Arms and Interventions

Arm Intervention/Treatment
Healthy controls (HCs)

Healthy controls (HCs)

Other: no intervention
no intervention

Emerged from Minimally Conscious State (EMCS)

Emerged from Minimally Conscious State (EMCS): recovery of functional object uses or communication from chronic

Other: no intervention
no intervention

Minimally conscious state (MCS)

Minimally conscious state (MCS): have reproducible signs of awareness and exhibit fluctuations in consciousness

Other: no intervention
no intervention

Vegetative state (VS)

Vegetative state (VS): can open their eyes and preserve sleep-wake cycles, but unaware of themselves and their surroundings

Other: no intervention
no intervention

Outcome Measures

Primary Outcome Measures

  1. Spectrum analysis of chronic disorders of consciousness [6 months]

    The EEG of 59 patients with disturbance of consciousness will be collected in resting state and listening to music, and the absolute power spectral density values (alpha,beta,theta,delta bands dB/Hz) will be calculated using spectral analysis.

  2. Duration of each microstate [6 months]

    The investigators conducted resting state EEG recordings on 59 patients with consciousness disorders and 32 healthy controls. The investigators refined the microstate method to accurately estimate topographical differences. The calculations were performed for measures of duration (ms). The duration of each microstate were utilized to predict disease classification and prognosis evaluation for patients with disturbance of consciousness.

  3. Occurrence of each microstate [6 months]

    The investigators conducted resting state EEG recordings on 59 patients with consciousness disorders and 32 healthy controls. The investigators refined the microstate analysis. The calculations were performed for measures of occurrence (times per minute). The occurrence of microstates were utilized to predict disease classification and prognosis evaluation for patients with disturbance of consciousness.

  4. Global explained variance (GEV) of each microstate [6 months]

    The investigators conducted resting state EEG recordings on 59 patients with consciousness disorders and 32 healthy controls. The investigators refined the microstate analysis. The calculations were performed for measures of GEV (%). The GEV of microstates were utilized to predict disease classification and prognosis evaluation for patients with disturbance of consciousness.

Secondary Outcome Measures

  1. Coma Recovery Scale-Revised(CRS-R) [30 minutes before samples collection]

    The Coma Recovery Scale-Revised (CRS-R) score was utilized to measure the severity of the condition. It comprises 23 items arranged hierarchically into six subscales, including auditory, visual, motor, oromotor/verbal, communication, and arousal processes. Reflexive activity is represented by the lowest item on each subscale, while cognitively mediated behaviors are portrayed by the highest items. The scale ranges from 0 (indicating the lowest level of consciousness) to 23 (indicating the highest level of consciousness). Generally, a higher score suggests a better level of consciousness, while a lower score suggests a lower level of consciousness.

  2. Glasgow Outcome Scale (GOS) [6 months]

    A GOS score ≥ 4 points is considered to indicate a good prognosis, while a GOS score < 4 points is considered to indicate a poor prognosis

Eligibility Criteria

Criteria

Ages Eligible for Study:
40 Years to 90 Years
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
Yes
Inclusion Criteria:
  1. Patients diagnosed with COMA /VS/MCS

  2. The course of disease was more than 4 weeks

  3. The vital signs were stable and able to tolerate the test process

  4. Complete skull

  5. Right-handed, no history of ear disease or hearing loss before onset

Exclusion Criteria:
  1. History of epilepsy

  2. Sedatives

  3. Muscle relaxants and epileptic prophylaxis within 24 hours

Contacts and Locations

Locations

Site City State Country Postal Code
1 Yi Ling Hangzhou Zhejiang China 310000

Sponsors and Collaborators

  • First Affiliated Hospital of Zhejiang University

Investigators

  • Study Chair: Benyuan Luo, Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
First Affiliated Hospital of Zhejiang University
ClinicalTrials.gov Identifier:
NCT05949528
Other Study ID Numbers:
  • EEG assessment
First Posted:
Jul 18, 2023
Last Update Posted:
Jul 18, 2023
Last Verified:
Oct 1, 2022
Individual Participant Data (IPD) Sharing Statement:
No
Plan to Share IPD:
No
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
Keywords provided by First Affiliated Hospital of Zhejiang University
Additional relevant MeSH terms:

Study Results

No Results Posted as of Jul 18, 2023