ArticleAnnals of biomedical engineering2019
Linking Joint Impairment and Gait Biomechanics in Patients with Juvenile Idiopathic Arthritis.
Article in Annals of biomedical engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed, 39 citations in OpenAlex.
- Markerless gait analysis for children and adolescents with juvenile idiopathic arthritis using a machine learning pipeline.Pediatric rheumatology online journal · 2026Article
- Gait Characteristics in Children with Juvenile Idiopathic Arthritis and Secondary Scoliosis.Children (Basel, Switzerland) · 2026Article
- EMG-Informed Neuromusculoskeletal Simulations Increase the Accuracy of the Estimation of Knee Joint Contact Forces During Sub-optimal Level Walking.Annals of biomedical engineering · 2025Article
- Balance Assessment in Juvenile Idiopathic Arthritis: A Literature Review.Life (Basel, Switzerland) · 2025Review
- Intra-operator Repeatability of Manual Segmentations of the Hip Muscles on Clinical Magnetic Resonance Images.Journal of digital imaging · 2023Article
- Association Between Patient-Reported Outcomes and Treatment Failure in Juvenile Idiopathic Arthritis.ACR open rheumatology · 2022Article
- Research progress in drug therapy of juvenile idiopathic arthritis.World journal of pediatrics : WJP · 2022Review
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Corrections and comments
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Authors and funding
14 authors at 6 institutions in 4 countries.
Funding
Abstract
Juvenile Idiopathic Arthritis (JIA) is a paediatric musculoskeletal disease of unknown aetiology, leading to walking alterations when the lower-limb joints are involved. Diagnosis of JIA is mostly clinical. Imaging can quantify impairments associated to inflammation and joint damage. However, treatment planning could be better supported using dynamic information, such as joint contact forces (JCFs). To this purpose, we used a musculoskeletal model to predict JCFs and investigate how JCFs varied as a result of joint impairment in eighteen children with JIA. Gait analysis data and magnetic resonance images (MRI) were used to develop patient-specific lower-limb musculoskeletal models, which were evaluated for operator-dependent variability (< 3.6°, 0.05 N kg
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Registered trials
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