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RECRUITING
NCT07890662
Prediction of SLE Flares Using Patient-Reported Outcomes and Machine Learning
Sponsor: Sohag University
View on ClinicalTrials.gov
Summary
This study aims to Develop a low-cost, PRO-based ML tool can: - Reduce lab costs - Enable telemedicine monitoring - Detect flares early - Improve care in resource-limited settings.
Key Details
Gender
All
Age Range
18 Years - 60 Years
Study Type
OBSERVATIONAL
Enrollment
500
Start Date
2026-06-30
Completion Date
2027-06-30
Last Updated
2026-10-22
Healthy Volunteers
Not specified
Conditions
Interventions
OTHER
Patient-Reported Questionnaire (PROs)
Fatigue, joint pain, morning stiffness, rash, oral ulcers, hair loss, fever, sleep, stress, medication adherence, flare history, patient global assessment (VAS 0-10)
Locations (1)
Sohag University
Sohag, Nasr City, Egypt