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A risk prediction model of postoperative cognitive dysfunction of cardiac surgery based on artificial intelligence fundus imaging recognition technology

A risk prediction model of postoperative cognitive dysfunction of cardiac surgery based on artificial intelligence fundus imaging recognition technology

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300073925
Enrollment
Unknown
Registered
2023-07-25
Start date
2023-08-01
Completion date
Unknown
Last updated
2023-07-30

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

Conditions

postoperative cognitive dysfunction

Interventions

Case series:none

Sponsors

Peking University First Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
45 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Age= 45 years old 2. Patients who intend to accept cardiac surgery

Exclusion criteria

Exclusion criteria: 1. Patients who cannot complete cognitive function examination due to neuropsychiatric diseases (such as schizophrenia and bipolar disorder) or Alzheimer's disease 2. Patients who cannot complete fundus imaging due to eye diseases such as cataracts and trauma 3. Patients undergoing neurosurgery at the same time

Design outcomes

Primary

MeasureTime frame
Fundus imaging recognition technology based on artificial intelligence;Incidence of POCD on day 5 postoperatively;Accuracy;—

Secondary

MeasureTime frame
The accuracy of AI fundus imaging recognition technology in predicting major cardiovascular adverse events up to 30 days after surgery;The accuracy of artificial intelligence fundus imaging recognition technology in predicting ischemic stroke within 30 days after surgery;—

Countries

China

Contacts

Public ContactDongliang Mu

Peking University First Hospital

mudongliang@icloud.com+86 178 1037 0608

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026