Clinical Pattern Recognition: Shoulder Pain at Mac App Store analyse

Clinical Pattern Recognition (CPR): Shoulder pain  (Updated for iOS 8! Make sure you update your device!) • A powerful comprehensive app linking research to clinical practice • Used in Residency and Fellowship training • Used by some of the top programs in the United States • Guideline based classification system for shoulder pain • Intuitive user interface that mimics the clinical reasoning of a master clinician • Common pain referral patterns link to common hypotheses including: - Frozen shoulder (Adhesive capsulitis) - Shoulder impingement (Subacromial pain syndrome) - Shoulder instability (SLAP lesion, Bankart lesion) - Thoracic outlet syndrome - Acromioclavicular joint sprain • Hypothesized conditions link to their specific key findings and faulty movements • Evidence based impairments are linked to their associated “ideal” interventions including:  - Manual therapy - Movement re-education - Therapeutic exercises - Modalities - Patient education • Includes region specific red flag conditions for emergent referral • Over 200 examination, movement analysis, manual therapy and exercise videos/pictures • Multi-angle, High definition video with instructions • Videos of how patients will present in the clinic  • Clinical reasoning videos for key findings, differential diagnosis, associated impairments, interventions and movement faults • Direct links to PUBmed abstracts for all techniques (where research is available) • Use clinical pattern recognition to develop your clinical reasoning “flow” or have quick access to all special tests/physical exam techniques, all manual therapy techniques or all exercise techniques Audience: • Physical therapists/Physiotherapists • Physical therapy assistants • Osteopathic physicians • Athletic trainers • Clinicians managing patients with musculoskeletal conditions • Medical professionals • Educators • Chiropractors • Anyone interested in rehabilitation for shoulder pain *This app may require you to be temporarily connected to wifi for downloading.