STEPWISE EVIDENCE BASED APPROACH OF CLINICAL EXAMINATION OF THE SHOULDER

Haupt-Bertschy B1, van den Boezem R2, Raniga S3, Zumstein M4
1Bern University Hospital, Physiotherapy, Bern, Switzerland, 2Applied Health Care, Bern, Switzerland, 3Macquarie University Hospital, Orthopaedics, Sydney, Australia, 4Bern University Hospital, Orthopaedics, Bern, Switzerland

Background: The appropriate management of patients with shoulder complaints is a significant challenge for physiotherapists because of the variety of underlying diagnoses. Defining an accurate diagnosis can be challenging for both, doctors and therapists. A reliable method of assessment is essential to obtain an accurate diagnosis and the subsequent provision of appropriate treatment. One of the most important aspects of managing these patients is to be able to recognize features that may require referral or a change in treatment strategy based on failure to progress, persisting pain or dysfunction. Hence, an inter-professional approach with physiotherapists and medical practitioners is essential. To our knowledge, there are no comprehensive clinical decision trees in the literature to guide the approach to shoulder problems.

Purpose: The aim was to develop, based on literature and experience, a clinical algorithm and to present and discuss his use to assess and manage patients with shoulder problems.

Methods: Based on the literature and on our own experience in the Berne University Hospital, Switzerland with the treatment of shoulder pathologies we developed a strategic inter-professional approach to this common presentation, in conjunction with specialist shoulder surgeons, rheumatologists and physiotherapists. In the literature, a confusing array of clinical tests can be found for a large variety of shoulder pathologies, whereof the clinician has to select for examination of the patient. Therefore, we tried to describe and define an algorithmic approach for the clinical reasoning to guide physiotherapists in the management of common shoulder problems. Based on the literature, we additionally defined certain yellow and red Flags, which might be checked in order to be able to refer patients in a timely manner.

Results: We present a simple but comprehensive state-of-the-art algorithm that allows the therapist to efficiently and accurately diagnose shoulder problems and to provide appropriate management. It is a dynamic algorithm, which encourages frequent reassessment to assess and validate an accurate diagnosis, which is independent of any specific physiotherapy modalities. It includes the examination of glenohumeral joint mobility, scapuladyskinesia and glenohumeral centering with specific tests. The tests are divided into three parts - the adjacent joints, examination of the nervous system as well as the common orthopedic tests for impingement, instability, acromioclavicular and sternoclavicular joint, the rotator cuff and biceps pathology. Each of the individual tests has been collated by literature, only the order and therapeutic consequences are based on experience and conviction.

Conclusion(s): In the literature many different shoulder test are described but little is reported about the interpretation and therapeutic consequences. Recommendations for the management of shoulder patients are lacking and thus the algorithm had to be completed based on our own clinical experience. The algorithm enables the physiotherapist to examine the patient in a single physiotherapy session and to determine then the best interventions and the main focus for the following therapy.

Implications: The application of this algorithm in daily clinical practice might help to improve the management and therapy of common shoulder pathologies by physiotherapist and other health practitioners.

Keywords: Physical examination, shoulder, musculoskeletal

Funding acknowledgements: This work was unfunded.

Topic: Musculoskeletal: upper limb; Orthopaedics

Ethics approval required: No
Institution: N/A
Ethics committee: N/A
Reason not required: Based on literature and experience we developed a new clinical algorithm.


All authors, affiliations and abstracts have been published as submitted.

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