The use of multidisciplinary assessment and scientific measurement in advanced juvenile idiopathic arthritis can categorise gait deviations to guide treatment. Issue 2 (1st August 2002)

• Record Type: Journal Article
• Authors: Fairburn, P S; Panagamuwa, B; Falkonakis, A; Osborne, S; Palmer, R; Johnson, B; Southwood, T R
• Is Part Of: Archives of disease in childhood. Volume 87:Issue 2(2002)
• Page Start: 160
• Page End: 165
• Publication Date: 2002-08-01
• Subjects: juvenile idiopathic arthritis -- multidisciplinary gait assessment -- ground reaction force -- dynamic plantar pressure; GRF, ground reaction force -- JIA, juvenile idiopathic arthritis -- MTH, metatarsal head -- MTJ, mid-tarsal joint -- MTPJ, metatarso-phalangeal joint -- PPP, peak plantar pressure -- ROM, range of motion -- STJ, subtalar joint -- VV, visual vector; Children -- Diseases -- Periodicals; Infants -- Diseases -- Periodicals; 618.920005
• DOI: 10.1136/adc.87.2.160
• Languages: English
• ISSNs: 0003-9888

Abstract

Abstract : Background: It is difficult to identify the range of gait deviations associated with juvenile idiopathic arthritis (JIA) using simple clinical observations. Aims: To use objective gait analysis to accurately describe biomechanical gait abnormalities in JIA and to search for common patterns, which may subsequently serve as a basis for therapeutic intervention. Methods: Children with persistent polyarticular arthritis and symmetrical joint involvement were referred to the Gait Analysis Laboratory and independently assessed by a multidisciplinary team. Gait analysis was performed using an in-house Visual Vector System and the Novel PEDAR in-shoe plantar pressure measurement system. Clinical groupings were based on the extent of joint restriction: minimal (group A), and moderate–severe (with supinatory foot deformity (group B), or with pronatory foot deformity (group C)). Gait analysis enabled classification of each subject into one of four gait patterns: either near normal (pattern I) or one of three adaptive patterns defined by the predominant abnormality—lower limb pain (pattern II), lower limb deformity (pattern III), or a combination of pain and deformity of the lower limb (pattern IV). Results: Of the 15 subjects assessed as part of this study, seven were placed into clinical group A, six into group B, and two into group C. All the subjects with gait patterns I and II were found in clinical group A. Both subjects from clinical group C exhibited gait pattern III. All subjects from clinical group B and the remainder from group A exhibited a mixture of gait patterns III and IV. Conclusion: Despite the initial clinical observations it was not always possible to predict the resultant gait pattern. Scientific gait analysis allowed a clear distinction to be made between primary and secondary gait deviations, and accurate targeting of physiotherapy and orthotic interventions to suit each individual. Prospective quantitative analysis in a larger sample is under way to support the clinical effectiveness of these findings.