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Predicting Forefoot-Orthosis Interactions in Rheumatoid Arthritis Using Computational Modelling.
Kelly, Emily S; Worsley, Peter R; Bowen, Catherine J; Cherry, Lindsey S; Keenan, Bethany E; Edwards, Christopher J; O'Brien, Neil; King, Leonard; Dickinson, Alex S.
Afiliação
  • Kelly ES; School of Engineering, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, United Kingdom.
  • Worsley PR; School of Health Sciences, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, United Kingdom.
  • Bowen CJ; School of Health Sciences, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, United Kingdom.
  • Cherry LS; School of Health Sciences, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, United Kingdom.
  • Keenan BE; Cardiff School of Engineering and Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom.
  • Edwards CJ; University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom.
  • O'Brien N; University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom.
  • King L; University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom.
  • Dickinson AS; School of Engineering, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, United Kingdom.
Front Bioeng Biotechnol ; 9: 803725, 2021.
Article em En | MEDLINE | ID: mdl-35004656
ABSTRACT
Foot orthoses are prescribed to reduce forefoot plantar pressures and pain in people with rheumatoid arthritis. Computational modelling can assess how the orthoses affect internal tissue stresses, but previous studies have focused on a single healthy individual. This study aimed to ascertain whether simplified forefoot models would produce differing biomechanical predictions at the orthotic interface between people with rheumatoid arthritis of varying severity, and in comparison to a healthy control. The forefoot models were developed from magnetic resonance data of 13 participants with rheumatoid arthritis and one healthy individual. Measurements of bony morphology and soft tissue thickness were taken to assess deformity. These were compared to model predictions (99th% shear strain and plantar pressure, max. pressure gradient, volume of soft tissue over 10% shear strain), alongside clinical data including body mass index and Leeds Foot Impact Scale-Impairment/Footwear score (LFIS-IF). The predicted pressure and shear strain for the healthy participant fell at the lower end of the rheumatoid models' range. Medial first metatarsal head curvature moderately correlated to all model predicted outcomes (0.529 < r < 0.574, 0.040 < p < 0.063). BMI strongly correlated to all model predictions except pressure gradients (0.600 < r < 0.652, p < 0.05). There were no apparent relationships between model predictions and instances of bursae, erosion and synovial hypertrophy or LFIS-IF score. The forefoot models produced differing biomechanical predictions between a healthy individual and participants with rheumatoid arthritis, and between individuals with rheumatoid arthritis. Models capable of predicting subject specific biomechanical orthotic interactions could be used in the future to inform more personalised devices to protect skin and soft tissue health. While the model results did not clearly correlate with all clinical measures, there was a wide range in model predictions and morphological measures across the participants. Thus, the need for assessment of foot orthoses across a population, rather than for one individual, is clear.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Bioeng Biotechnol Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Bioeng Biotechnol Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Reino Unido
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