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NCT Number: NCT07080307

Artificial Intelligence (AI)-Based Prediction of Treatment Response in Sciatica Patients Receiving Transforaminal Epidural Steroid Injection

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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Key information

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age 18 years or older
  • Presence of clinical and radiological radiculopathy findings consistent with L4, L5, or S1 nerve root involvement
  • Symptoms present for at least 3 months
  • Resistant to conservative treatment
  • Scheduled for transforaminal epidural steroid injection (TFESI) by a pain medicine specialist
  • Being willing to participate in the study and having signed a consent form

Exclusion criteria

  • Malignancy
  • Coagulation disorders
  • Pregnancy
  • History of allergic reaction to the injected substances
  • History of major psychiatric disorders
  • Presence of known coagulopathy
  • Receiving systemic steroid treatment for any reason
  • Having received an epidural steroid injection within the last 3 months

Treatment and study plan

Primary outcomes

  1. Change in pain intensity measured by Numeric Rating Scale (NRS)

    Time frame: Baseline, 1 hour, 3 months, 6 months after TFESI

    Pain intensity will be assessed using the Numeric Rating Scale (0-10). A reduction of ≥50% from baseline will be considered a positive treatment response.

  2. Change in functional status measured by Oswestry Disability Index (ODI)

    Time frame: Baseline, 3 months, 6 months

    Functional disability will be assessed using the validated ODI questionnaire.

Secondary outcomes

  1. Change in psychological status measured by Beck Depression Inventory (BDI)

    Time frame: Depression symptoms will be evaluated using BDI to assess changes related to pain improvement.

    Baseline, 3months and 6 months

  2. Change in health-related quality of life measured by SF-12

    Time frame: Baseline, 3 months and 6 months

    SF-12 will be used to assess the impact of pain and treatment on quality of life.

Study contacts

Contact information is provided by the study sponsor or research team.

Faruk Kargıoğlu, Asisstant Doctor

CONTACT

[email protected]

+905304774375

Savaş Şencan, Associate Professor

CONTACT

[email protected]

+905370665713

Sponsors and collaborators

Lead sponsor

Marmara University

Other

Registry information

Official study title

Artificial Intelligence-Based Predictive Models for Estimating Treatment Response in Sciatica Patients Treated With Transforaminal Epidural Steroid Injection (TFESI)

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Jul 23, 2025
Registry last updated
Jul 23, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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