Clinical Pattern Recognition: Knee pain for iOS

Used Clinical Pattern Recognition: Knee pain for iOS?

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Clinical Pattern Recognition (CPR): Knee pain (Updated for iOS 8, Make sure you have updated your device!) A powerful comprehensive app linking...

Clinical Pattern Recognition (CPR): Knee pain (Updated for iOS 8, Make sure you have updated your device!) A powerful comprehensive app linking research to clinical practice Guideline based classification system for knee pain Intuitive user interface that mimics the clinical reasoning of a master clinician Common pain referral patterns link to common hypotheses including: - Knee osteoarthritis - Patellofemoral pain syndrome - Knee meniscal tears - Knee anterior cruciate ligament tears - Iliotibial band syndrome - Medial collateral ligament sprains Hypothesized conditions link to their specific key findings and faulty movements Evidence based impairments are linked to their associated ideal intervention including: - Manual therapy - Movement re-education - Therapeutic exercises - Modalities - Patient education Includes region specific red flag conditions for emergent referral Over 300 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 see develop your clinical reasoning flow or have quick access to all special tests/physical exam techniques, all manual therapy techniques or all exercise techniquesAudience: 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 knee pain*This app may require you to be temporarily connected to wifi for downloading.