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Rotator cuff tears are one of the most common causes of shoulder pain. Evidence-based guidance on optimal diagnostic and treatment strategies for rotator cuff tears is lacking. Our proposed study aims to fill these gaps by identifying the prognostic factors which will predict better outcomes of rotator cuff tears, based on both operative and non-operative treatment. The investigators will also compare outcomes of operative and non-operative treatment of rotator cuff tears and report on the best way to diagnose rotator cuff tears.
Full description
Rotator cuff tears account for over one quarter million surgeries annually. They are a leading cause of shoulder pain and disability. Patients with rotator cuff tears present with shoulder pain and/or limitation in range of motion. Fourteen special physical exam tests have been described for diagnosis of rotator cuff tears. Prior literature describing sensitivity and specificity of these tests in diagnosing cuff tears is limited by retrospective design, small sample sizes, samples restricted to patients undergoing surgery, and failure to differentiate between partial and full thickness tears. As a result, there is little evidence to help clinicians interpret the diagnostic value of the clinical exam. Consequently, clinicians rely heavily on magnetic resonance imaging (MRI) for diagnosing cuff tears, adding considerable expense in the diagnostic process.
The treatment options for rotator cuff tears are operative and non-operative. There is currently little consensus on indications and timing of rotator cuff surgery or non-operative treatment. Furthermore, there is lack of evidence-based guidance on factors associated with outcomes of operative versus non-operative treatment for cuff tears.
We are enrolling patients in a prospective cohort study to assess comparative-effectiveness of operative versus non-operative treatment of rotator cuff tears and understand prognostic factors for better outcomes after surgery and non-operative treatments.
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Data sourced from clinicaltrials.gov
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