Skip to content

To establish and verify the application value of deep learning technology in the early prediction of vascular cognitive impairment and its outcome

To establish and verify the application value of deep learning technology in the early prediction of vascular cognitive impairment and its outcome

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200058602
Enrollment
Unknown
Registered
2022-04-12
Start date
2022-05-01
Completion date
Unknown
Last updated
2024-01-08

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

Conditions

Healthy subjects or stroke patients

Interventions

Sponsors

The Seventh Affiliated Hospital, Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Aged over 18 years; 2. Healthy subjects or patients diagnosed as stroke for the first time (no history and symptoms related to cognitive impairment before stroke); 3. The subjects voluntarily participated in and completed the project, signed the informed consent form and completed the case report form.

Exclusion criteria

Exclusion criteria: 1. Unstable vital signs, combined with serious chronic diseases of heart, brain, liver, kidney and other important organs; 2. There are contraindications to fundus photography, and fundus photography cannot be completed; 3. The subject asked to withdraw halfway and voluntarily withdrew the informed consent.

Design outcomes

Primary

MeasureTime frame
Montreal Cognitive Assessment Scale;Clinical Dementia Rating Scale;eye-ground photography;Systolic blood pressure;diastolic blood pressure;Fasting blood glucose;Glycosylated hemoglobin;Total cholesterol;low density lipoprotein;serum uric acid;hyperhomocysteine;

Countries

China

Contacts

Public ContactZhang Qian

The Seventh Affiliated Hospital, Sun Yat-sen University

zhangq_rehab@163.com+86 15017554589

Outcome results

None listed

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