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
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Disorders of Consciousness
- Sponsor
- First Affiliated Hospital of Zhejiang University
- Enrollment
- 200
- Locations
- 1
- Primary Endpoint
- Duration of each microstate
- Status
- Recruiting
- Last Updated
- 2 years ago
Overview
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.
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.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Patients diagnosed with COMA /VS/MCS
- •The course of disease was more than 4 weeks
- •The vital signs were stable and able to tolerate the test process
- •Complete skull
- •Right-handed, no history of ear disease or hearing loss before onset
Exclusion Criteria
- •History of epilepsy
- •Muscle relaxants and epileptic prophylaxis within 24 hours
Outcomes
Primary Outcomes
Duration of each microstate
Time Frame: 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.
Spectrum analysis of chronic disorders of consciousness
Time Frame: 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.
Occurrence of each microstate
Time Frame: 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.
Global explained variance (GEV) of each microstate
Time Frame: 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 Outcomes
- Glasgow Outcome Scale (GOS)(6 months)
- Coma Recovery Scale-Revised(CRS-R)(30 minutes before samples collection)