Ultrasound-guided Needle Percutaneous Electrolysis With Therapeutic Exercise in Femoroacetabular Impingement Syndrome

Femoroacetabular impingement is a common cause of anterior hip pain in young and middle-aged adults. This condition involves abnormal mechanical contact between the proximal femur and the acetabular rim, which can lead to labral damage, cartilage injury, and pain. Soft tissue structures, particularly the iliopsoas tendon and its relationship with the anterior capsulolabral complex, frequently contribute to the symptoms. Ultrasound-guided percutaneous electrolysis is a minimally invasive technique used in physiotherapy. It involves the application of a controlled galvanic current through a fine needle inserted under ultrasound guidance into targeted soft tissues, with the aim of reducing pain and promoting tissue repair. This randomized pilot clinical trial will compare the effectiveness and safety of ultrasound-guided percutaneous electrolysis combined with a therapeutic exercise program versus the same therapeutic exercise program alone in participants with anterior hip pain compatible with femoroacetabular impingement. Eligible participants will be randomly allocated to one of two parallel groups. Both groups will follow a standardized home-based exercise program focused on hip mobility, gluteal strengthening, core stability, and controlled hip flexor activation. The experimental group will additionally receive two sessions of ultrasound-guided percutaneous electrolysis, performed one week apart. Primary and secondary outcomes will include pain intensity during provocative tests, hip range of motion to the first onset of pain, and self-reported hip function. All outcome assessments will be conducted by a blinded evaluator at baseline, one week, and four weeks after the first intervention session. Adverse events will be systematically recorded. The results of this pilot study will provide preliminary evidence regarding the potential additive benefit of percutaneous electrolysis to exercise therapy and will inform the design and sample size calculation of future larger-scale randomized controlled trials