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This study evaluates the effectiveness of a specific manual therapy approach based on the Algo-K decision algorithm in patients with subacute low back pain radiating to the lower limb. Algo-K helps select the most suitable lumbar mobilization technique according to the patient's pain response. The experimental group will receive a five-minute targeted manual therapy in addition to standard physiotherapy, while the control group will receive a non-specific mobilization. The study aims to determine whether this algorithm-guided intervention leads to faster and greater improvement in pain and disability.
Full description
Subacute low back pain (LBP) with radiating symptoms is a common musculoskeletal disorder with a risk of chronicization. Manual therapy is often used in physiotherapy to treat LBP, but its effectiveness varies widely due to heterogeneous practices and lack of specificity. The Algo-K algorithm was developed to guide therapists in selecting the most appropriate mobilization technique based on patients' symptomatic responses during movement tests.
This multicenter randomized controlled trial compares the effectiveness of a specific manual therapy guided by the Algo-K algorithm versus a non-specific manual therapy added to a standardized exercise-based physiotherapy program. Sixty adult patients with subacute LBP and radiating pain will be included. Participants will be randomly assigned to either:
Both groups will receive the same standard physiotherapy care based on exercise and education, delivered over 12 sessions within a 60-day period.
The primary outcome is the Oswestry Disability Index (ODI) score at 26-30 days. Secondary outcomes include pain intensity (Numeric Rating Scale), pain distribution (body diagram), and long-term disability (ODI at 52-60 days). The hypothesis is that the specific, patient-tailored manual therapy will improve functional outcomes and reduce pain more effectively than non-specific mobilization.
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60 participants in 2 patient groups
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Romain ARTICO, PhD; Sebastien MARTIN, PT, MSc
Data sourced from clinicaltrials.gov
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