Developing an algorithm for classification of people with sciatica in the Greek health system
- Conditions
- SciaticaMusculoskeletal Diseases
- Registration Number
- ISRCTN14792164
- Lead Sponsor
- niversity of West Attica
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Ongoing
- Sex
- All
- Target Recruitment
- 300
1. Patients with sciatica diagnosed by spine specialist in a private or public hospital and referred to physiotherapy
2. Pain in the lumbar region that reflects at the lower extremity in either a dermatomal distribution or not
3. Subjective neurological symptoms in one lower extremity, such as numbness, tingling, burning, weight sensation and crippling pain
4. Aged 18-75 years old
5. Ablity to read and communicate in Greek
6. Willingness to participate in the study
1. Suspected serious spinal pathology or clinical red-flags such as cauda equina syndrome, suspicion of spinal tumours, infection, fractures and inflammatory spondyloarthropathy
2. Previous lumbar spine surgery
3. Previous lower extremity surgery
4. Currently receiving ongoing care from or have been in consultation with a secondary care doctor or physiotherapist for the same problem in the last 3 months
5. Serious co-morbidity preventing them from attending the research clinic and/or undergoing assessment and interventions
6. Severe enduring mental health condition
7. Pregnancy
8. Current participation in any other research study because of symptoms of back and leg pain or sciatica
9. Scoliosis of the spine >10 degrees, as measured on an X-ray
10. Taking steroid medications to treat neurological symptoms during the research period
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Development of an algorithm to categorize patients as low, medium and high-risk based on their sciatica symptoms assessed by questionnaires, neurologic examination, and neurodynamics evaluation at baseline without follow up
- Secondary Outcome Measures
Name Time Method