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A predictive model for cognitive progression of Parkinson's disease based on multi-dimensional information machine learning algorithms

A predictive model for cognitive progression of Parkinson's disease based on multi-dimensional information machine learning algorithms

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500099982
Enrollment
Unknown
Registered
2025-04-01
Start date
2025-09-01
Completion date
Unknown
Last updated
2025-04-07

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

Conditions

Parkinson's disease

Interventions

Observation group:None

Sponsors

Beijing hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
50 Years to 80 Years

Inclusion criteria

Inclusion criteria: (1) 50-80 years old (2) meet the diagnostic criteria of clinically definite or clinically probable Parkinson's disease based on Chinese diagnostic criteria (2016) or Movement Disorder Society criteria (2015) (3) early stage (Hoehn Yahr stage <= 2.5)

Exclusion criteria

Exclusion criteria: (1) Diagnosed with parkinsonism other than primary Parkinson's disease, or patients with unclear diagnosis (2) History of stroke or intracranial tumor in the past (3) Patients with ophthalmic diseases that have previously affected eye movement (4) Any neurological disorder or musculoskeletal injury that interferes with gait or balance other than Parkinson's motor symptoms (such as fractures, stroke sequelae, etc.) (5) Suffering from serious organic diseases such as advanced tumors, with an expected life expectancy of no more than 2 years (6) Patients with mental illness or other reasons cannot cooperate (7) Simultaneously undergoing other clinical trials (8) Due to geographical reasons, the requested treatment and follow-up cannot be accepted

Design outcomes

Primary

MeasureTime frame
Montreal Cognitive Assessment;

Secondary

MeasureTime frame
Cognitive status;Trail Making Test A and B;digit span test;Boston Naming Test;Semantic similarity testing;Language fluency test;World Health Organization California Auditory Word Learning Test;clock drawing test;

Countries

China

Contacts

Public ContactHuimin Chen

Beijing hospital

Huimin_Chen01@163.com+86 155 0103 7242

Outcome results

None listed

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