This prospective observational study aims to develop artificial intelligence (AI)-based predictive models to estimate treatment response in patients with sciatica undergoing transforaminal epidural steroid injection (TFESI). Approximately 1500 adult patients diagnosed with sciatica and scheduled for TFESI at Marmara University Training and Research Hospital Algology Clinic will be enrolled. Clinical, radiological, laboratory, and psychological data will be systematically collected before the procedure and at multiple follow-up points (1 hour, 3 weeks, 3 months, and 6 months post-treatment). Pain relief, measured by a 50% or greater reduction in the Numeric Rating Scale (NRS), will be the primary outcome. The study will use these comprehensive data sets to train and validate AI algorithms, aiming to create a decision-support system that can predict individual patient responses to TFESI and improve personalized treatment planning.
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Change in pain intensity measured by Numeric Rating Scale (NRS)
Timeframe: Baseline, 1 hour, 3 months, 6 months after TFESI
Change in functional status measured by Oswestry Disability Index (ODI)
Timeframe: Baseline, 3 months, 6 months