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A cohort study and prediction model construction of fatigue degree in rheumatoid arthritis based on machine learning

A cohort study and prediction model construction of fatigue degree in rheumatoid arthritis based on machine learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500101333
Enrollment
Unknown
Registered
2025-04-23
Start date
2025-05-01
Completion date
Unknown
Last updated
2025-04-28

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

Conditions

Rheumatoid arthritis

Interventions

Non-exposed group:None
Exposure group:None

Sponsors

Dongzhimen Hospital, Beijing University of Chinese Medicine
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 72 Years

Inclusion criteria

Inclusion criteria: 1.Age of 18-72 years old,male or female.2.The patient met the diagnostic criteria for rheumatoid arthritis and fatigue.3.Patients who visited more than 2 times and had complete medical records.

Exclusion criteria

Exclusion criteria: 1.Combined with other rheumatic diseases that may affect the fatigue assessment,including but not limited to systemic lupus erythematosus,Sjogren's syndrome,systemic scleroderma,fibromyalgia syndrome,ankylosing spondylitis,etc.2.patients with established fatigue syndrome.3.Complicated with severe respiratory diseases,cardiovascular and cerebrovascular diseases.4.Known mental illness,or allergic constitution.5.Patients with incomplete case data.

Design outcomes

Primary

MeasureTime frame
Degree of fatigue;

Secondary

MeasureTime frame
TCM syndrome;Disease activity situation;Erythrocyte sedimentation rate;High-sensitivity C-reactive protein;Anti-cyclic citrullinated peptide Antibody;Rheumatoid Factor;Immunoglobulin G;Immunoglobulin M;Immunoglobulin A;Number of swollen joints;Joint tenderness counts;Duration of morning stiffness;Degree of pain;

Countries

China

Contacts

Public ContactLv Liu

Dongzhimen Hospital, Beijing University of Chinese Medicine

984193184@qq.com+86 132 1200 7957

Outcome results

None listed

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