Risk Warning Model of Postoperative Delirium and Long-term Cognitive Dysfunction in Elderly Patients
Risk Warning Model of Postoperative Delirium and Long-term Cognitive Dysfunction in Elderly Patients Based on Autonomous Evolutionary Neural Network Algorithm
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: lei zhao
- Phone Number: +8613811035886
- Email: zhaoalei@sina.com
Study Contact Backup
- Name: xia li li
- Phone Number: +86818810616341
- Email: 935496838@qq.com
Study Locations
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Beijing, China, 100053
- Recruiting
- Xuanwu Hospital, Capital Medical University
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Contact:
- Lei Zhao, Doctor's
- Phone Number: +8613811035886
- Email: zhaoalei@sina.com
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Contact:
- Lixia Li, Master's
- Phone Number: +86818810616341
- Email: 935496838@qq.com
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Patients ≥65 years of age who have undergone surgical anesthesia; Sign informed consent
Exclusion Criteria:
- Inability to complete cognitive function assessment; Illiteracy, hearing impairment or visual impairment; He has a history of epilepsy, depression, schizophrenia, Alzheimer's disease and other psychiatric and neurological diseases
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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postoperative delirium(POD) and postoperative neurocognitive disorder(pNCD)
Delirium (CAM scale ) was assessed 7 days after surgery and divided into POD and non-POD groups; one of the above scenarios indicated postoperative delirium;The patients in the POD group were evaluated for cognitive function at 1 month and 12 months after surgery to determine whether pNCD occurred.
The patients in the POD group were further divided into pNCD subgroup and non-PNCD subgroup, and EEG data collection and fMRI scanning were performed
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this is an observation study,no intervention
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Screening for risk factors of perioperative cognitive dysfunction
Time Frame: 2024.4.1-2027.12.31
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The feature selection technique in artificial intelligence was used to screen and analyze data from a large dataset of clinical care after fusion The risk factors with the highest probability of PND occurrence can be screened from a large number of characteristics,By screening the risk factors that have the highest correlation with the probability of POD occurrence, combined with the comparison of fMRI imaging data of different groups of large sample size POD patients with long-term conversion to pNCD group and non-PNCD group, the brain network mechanism and perioperative high risk factors of POD conversion to long-term cognitive dysfunction were further explored.
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2024.4.1-2027.12.31
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Establish a prediction system for adverse brain function events
Time Frame: 2025.1.1-2027.12.31
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The monitoring data of surgical patients contains a large amount of medical information, and the analysis and modeling of the data can provide effective early warning and intervention.
The project intends to adopt EEG time-frequency feature extraction and analysis, EEG micro-state analysis, and brain network analysis, and adopt feature fusion technology to fuse various features into unified features of patients.
On this basis, a prediction model of adverse brain function events based on domain adaptation algorithm was constructed to realize real-time tracking, early diagnosis and early warning of postoperative delirium and long-term cognitive dysfunction in elderly patients
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2025.1.1-2027.12.31
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Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Study Chair: lei zhao, xuanwu hospital of capital medical university,Beijing
- Principal Investigator: yong yang, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences
- Principal Investigator: yi an, xuanwu hospital of capital medical university,Beijing
- Principal Investigator: xia li li, xuanwu hospital of capital medical university,Beijing
- Principal Investigator: yang liu, xuanwu hospital of capital medical university,Beijing
- Principal Investigator: yi shu yang, xuanwu hospital of capital medical university,Beijing
Publications and helpful links
General Publications
- Patel A, Zhang M, Liao G, Karkache W, Montroy J, Fergusson DA, Khadaroo RG, Tran DTT, McIsaac DI, Lalu MM. A Systematic Review and Meta-analysis Examining the Impact of Age on Perioperative Inflammatory Biomarkers. Anesth Analg. 2022 Apr 1;134(4):751-764. doi: 10.1213/ANE.0000000000005832.
- An Y, Zhao L, Wang T, Huang J, Xiao W, Wang P, Li L, Li Z, Chen X. Preemptive oxycodone is superior to equal dose of sufentanil to reduce visceral pain and inflammatory markers after surgery: a randomized controlled trail. BMC Anesthesiol. 2019 Jun 11;19(1):96. doi: 10.1186/s12871-019-0775-x.
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 62376168
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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