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Machine learning-based analysis of EEG data to identify different sources of adverse stimuli in general anesthesia patients during recovery

Machine learning-based analysis of EEG data to identify different sources of adverse stimuli in general anesthesia patients during recovery

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600123109
Enrollment
Unknown
Registered
2026-04-21
Start date
2026-02-01
Completion date
Unknown
Last updated
2026-04-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Emergence Agitation

Interventions

Observation group:None

Sponsors

The First Affiliated Hospital of the School of Medicine, Zhejiang University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
25 Years to 65 Years

Inclusion criteria

Inclusion criteria: 1. Adult patients aged between 25 and 65 years. 2. Normal growth, development, and intellectual capacity. 3. Undergoing surgical procedures under endotracheal tube general anesthesia. 4. Utilization of BIS (Bispectral Index) monitoring during general anesthesia.

Exclusion criteria

Exclusion criteria: 1. History of central nervous system disorders such as epilepsy. 2. Undergoing craniocerebral surgery or having a history of preoperative consciousness disorders. 3. Difficult airway. 4. Occurrence of allergic reactions during the surgery. 5. Body Mass Index (BMI) > 26 kg/m^2. 6. Anemia (Hemoglobin < 7 g/dL). 7. Thyroid dysfunction (hypothyroidism or hyperthyroidism). 8. Patients unable to cooperate or who refuse EEG monitoring preoperatively.

Design outcomes

Primary

MeasureTime frame
EEG Power;AUC of machine learning model;

Secondary

MeasureTime frame
Ramsay Score;Total opioid analgesic consumption;

Countries

China

Contacts

Public ContactYu Zhang

The First Affiliated Hospital of the School of Medicine, Zhejiang University

54386067@qq.com+86 571 8723 6685

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: May 1, 2026