Association of Perioperative Electroencephalography Spectral Analysis With Postoperative Complications

NCT ID: NCT05818163

Last Updated: 2023-04-18

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 100 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2023-05-31
• Study Completion Date: 2023-12-31

Brief Summary

Using data from electroencephalogram (EEG) obtained through intraoperative depth of anesthesia monitoring devices, combined with clinical symptoms such as postoperative pain and delirium, investigate their correlation and verify whether intraoperative EEG spectral analysis can predict the occurrence of postoperative pain, nausea and vomiting, restlessness, or delirium in patients undergoing surgery.

Detailed Description

Due to the complexity of the original EEG waveforms, previous anesthesia depth monitoring systems only calculated a single index, such as Bispectral index (BIS) or patient state index (PSI), to determine the state under anesthesia. However, a single numerical change may not reflect the true state under anesthesia. By analyzing the original EEG waveforms, more information can be obtained, such as density spectral array (DSA) and power spectral density, which can quantify the energy distribution at various brain wave frequencies. This allows anesthesiologists to determine the effects of medication on brain waves and the effects of surgical stimulation on brain waves during surgery.

After obtaining the signed informed consent form, before inducing general anesthesia in the patient entering the operating room, an anesthesia depth monitoring patch is attached to the forehead, and EEG data during anesthesia is collected using the currently used anesthesia depth monitoring device. The monitoring process starts from the beginning of general anesthesia until the end of the surgery, and the EEG recording is stopped only when the patient wakes up from general anesthesia and leaves the operating room.

By using the original EEG during anesthesia depth monitoring to conduct spectral analysis and combining it with common post-anesthesia adverse symptoms such as pain, nausea and vomiting, delirium, and restlessness, a correlation analysis is conducted between the quantified EEG values and postoperative symptoms. This verifies whether intraoperative EEG spectral analysis can predict the occurrence of postoperative complications.

Conditions

Anesthesia; Pain; EEG

Study Design

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

Study Groups

with postoperative complications

Patients who experience postoperative complications after anesthesia, with symptoms such as pain, nausea and vomiting, delirium, and agitation.

electroencephalography spectral analysis

Intervention Type: DEVICE

Before inducing general anesthesia in the patient entering the operating room, an anesthesia depth monitoring patch is attached to the forehead, and EEG data during anesthesia is collected using the currently used anesthesia depth monitoring device.

The EEG data is transformed into a frequency and energy distribution and density spectral array (DSA) graph using Fourier transform (FFT) for spectral analysis.

without postoperative complications

Patients who do not experience postoperative complications after anesthesia, free from symptoms such as pain, nausea and vomiting, delirium, and agitation.

electroencephalography spectral analysis

Intervention Type: DEVICE

Before inducing general anesthesia in the patient entering the operating room, an anesthesia depth monitoring patch is attached to the forehead, and EEG data during anesthesia is collected using the currently used anesthesia depth monitoring device.

The EEG data is transformed into a frequency and energy distribution and density spectral array (DSA) graph using Fourier transform (FFT) for spectral analysis.

Interventions

electroencephalography spectral analysis

Before inducing general anesthesia in the patient entering the operating room, an anesthesia depth monitoring patch is attached to the forehead, and EEG data during anesthesia is collected using the currently used anesthesia depth monitoring device.

The EEG data is transformed into a frequency and energy distribution and density spectral array (DSA) graph using Fourier transform (FFT) for spectral analysis.

Intervention Type: DEVICE

Other Intervention Names

density spectral array; patient state index (PSI)

Eligibility Criteria

Inclusion Criteria

1. Aged 20 years or older.

2. Patients who received general anesthesia within the our hospital system.

Exclusion Criteria

1. Individuals with suspected infections, such as a fever higher than 38.3℃

2. Individuals with renal dysfunction, such as those with creatinine levels higher than 1.5 or those who require long-term dialysis

3. Individuals with cardiac dysfunction, such as those with NYHA class III or higher heart failure or coronary heart disease Individuals with neurological diseases, such as those with brain tumors, dementia, stroke, or epilepsy

4. Vulnerable populations, such as minors (under 20 years of age), pregnant women and fetuses, prisoners, adults who cannot give informed consent, individuals with disabilities, individuals with mental illness, residents of nursing homes or long-term care facilities, or those who may be subject to coercion or unable to make decisions freely.

• Minimum Eligible Age: 20 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

National Taiwan University Hospital

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

National Taiwan University, Cancer Center

Taipei, , Taiwan

Site Status: RECRUITING

Countries

Taiwan

Central Contacts

Chung Chih Shih, MD

Role: CONTACT

s6319138@gmail.com

886-2312-3456

Facility Contacts

Chung Chih Shih

Role: primary

s6319138@gmail.com

023123456

Other Identifiers

202208066DINA

Identifier Type: -

Identifier Source: org_study_id