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Recruiting NCT07890662

Prediction of SLE Flares Using Patient-Reported Outcomes and Machine Learning

Conditions: SLE

Sex: All

Ages: 18 Years – 60 Years

Enrollment: 500

Sponsor: Sohag University

Location: Sohag University Sohag Nasr City

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.

Eligibility Criteria

Inclusion Criteria: * Age ≥ 18 years. • Both sexes. • Patients diagnosed with SLE who fulfilling the Systemic Lupus 2019 European League against Rheumatism/American College of rheumatology classification criteria for systemic lupus erythematosus (2019 EULAR/ACR SLE classification criteria) • Regular follow up. Exclusion Criteria: * • Co-existing chronic inflammatory or autoimmune diseases. • Age \

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View on ClinicalTrials.gov

Source: ClinicalTrials.gov (NCT07890662). StuddyBuddy aggregates publicly available trial information.