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A Treatment-Based Classification Algorithm to Treat Achilles Tendinopathy: An Exploratory Case Series
Journal of Sport Rehabilitation
|November 12, 2016
Summary
This study found that a treatment-based-classification (TBC) algorithm effectively reduced pain and disability for Achilles tendinopathy patients. The TBC approach offers a promising alternative to traditional eccentric exercises for managing this common condition.
Area of Science:
- Orthopedics
- Sports Medicine
- Rehabilitation Science
Background:
- Achilles tendinopathy is prevalent in general and athletic populations.
- Current standard treatment, eccentric exercise, is often painful and time-consuming.
- Indirect treatment approaches for tendinopathy show potential for fewer, pain-free treatments.
Purpose of the Study:
- To evaluate the effectiveness of a treatment-based-classification (TBC) algorithm for Achilles tendinopathy.
- To determine if TBC improves patient outcomes compared to standard care.
Main Methods:
- A case series design involving 11 participants diagnosed with Achilles tendinopathy.
- Participants were assessed and treated across multiple clinics.
- Outcome measures included Numeric Rating Scale (NRS), DPA Scale, VISA-A, GRC, and Nirschl Phase Rating Scale.
Main Results:
- Analysis of NRS scores showed significant improvement from initial exam to discharge and follow-up.
- Paired t-tests indicated effectiveness of the TBC algorithm on DPA Scale and VISA-A scores.
- Descriptive statistics on GRC demonstrated positive participant-reported outcomes.
Conclusions:
- The TBC algorithm demonstrated efficacy in improving function for Achilles tendinopathy patients.
- This approach led to decreased pain and disability in the study cohort.
- TBC offers a viable, potentially less painful, treatment strategy for Achilles tendinopathy.
