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Construction and validation of a clinical prediction model for fibromyalgia syndrome in children based on machine Learning

Construction and validation of a clinical prediction model for fibromyalgia syndrome in children based on machine Learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500115241
Enrollment
Unknown
Registered
2025-12-24
Start date
2026-01-01
Completion date
Unknown
Last updated
2026-01-05

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

Conditions

Fibromyalgia syndrome

Interventions

Gold Standard:The diagnostic criteria for FMS revised by the American College of Rheumatology (ACR) in 2016
Index test:Clinical prediction model based on machine learning

Sponsors

Children's Hospital of Chongqing Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
6 Years to 18 Years

Inclusion criteria

Inclusion criteria: 1.Children who visited the pain Clinic of Children's Hospital Affiliated to Chongqing Medical University between June 2023 and December 2030; 2.Patients in the non-FMS chronic pain control group were included: those diagnosed with the following diseases (rheumatoid arthritis, systemic lupus erythematosus, polyarticular osteoarthritis, polymyalgia rheumatica, polymyositis or other myopathy, spondyloarthropathy, multiple sclerosis); 3.Patients in the FMS patient group were included: children diagnosed with FMS; 4.Aged 6 to 18;

Exclusion criteria

Exclusion criteria: 1.The child patient has mental illness or cognitive impairment; 2.Recently (within 3 months) received treatments that may affect the FMS assessment, such as immunosuppressive therapy, severe pain management, etc; 3.Children with retrospective data missing more than 30% (more than 30% of the key variables to be collected and analyzed in this study were missing, inaccessible or poorly recorded); 4.Acute or chronic pain diseases (such as trauma, organic diseases, etc.) for differential diagnosis of non-fibromyalgia; 5.Children with serious diseases in other systems, such as cardiovascular diseases, respiratory system diseases, hematological malignancies, diabetes, etc; 6.The family of the child refused.

Design outcomes

Primary

MeasureTime frame
Questionnaire survey;Accuracy;

Secondary

MeasureTime frame
Sensitivity;Specificity;

Countries

China

Contacts

Public ContactTu Shengfen

Children's Hospital of Chongqing Medical University

519194496@qq.com+86 23 6848 6646

Outcome results

None listed

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