Patient characteristics predicting treatment success of shockwave therapy combined with physical therapy in plantar fasciopathy: An observational cohort study

Abstract

Introduction: Shockwave therapy is increasingly used by physical therapists for the treatment of plantar fasciopathy with varying success. The success of shockwave therapy in plantar fasciopathy depends on several factors. Therefore, the aim of this study is to identify patient characteristics predicting treatment success of shockwave therapy combined with physical therapy in plantar fasciopathy.

Methods: An observational cohort study was conducted of 54 participants. At weekly intervals participants were treated with 4 sessions of radial shockwave therapy using a standardized protocol accompanied by a physical therapy regimen. Six baseline characteristics (age, gender, duration of complaints, pain at rest, episode number and presence of calcification) were investigated for their prognostic ability on treatment success according to the 7-point Likert scale at 6 weeks follow-up. Data were analysed using bivariate and multivariate logistic regression analysis.

Results: According to the 7-point Likert scale 44 participants (81.5%) were treated successfully with shockwave therapy combined with physical therapy. Bivariate analysis showed significant associations between treatment success and gender, pain at rest, and duration of complaints (p<0.2). Multivariate logistic regression analysis showed that treatment success at 6 weeks follow-up was predicted by duration of complaints (p<0.05). Patients with complaints for less than 12 months are 4.5 times more likely to experience a successful treatment than patients with complaints for 12 or more months.

Conclusion: The present observational cohort study showed that treatment success of shockwave therapy combined with physical therapy can be predicted by duration of complaints at baseline, indicating that patients suffering for less than 12 months were more successfully treated than those with complaints over 12 months. Identification of predicting factors may help clinicians to determine which patients are most likely to benefit from an intervention.