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Objective assessment of dyskinesia in children with cerebral palsy
J R Davids1, T Foti, J Dabelstein
1Motion Analysis Laboratory, Shriners Hospital for Children, Greenville, South Carolina 29605, USA. jrdmd@greenville.infi.net
Insights
Computer analysis of gait objectively identifies dyskinetic cerebral palsy. This method distinguishes dyskinetic from spastic cerebral palsy, improving treatment predictability for children with cerebral palsy.
Area of Science:
- Biomedical Engineering
- Orthopedics
- Neurology
Background:
- Clinical classification of cerebral palsy (CP) faces limitations.
- Accurate differentiation between spastic and dyskinetic CP is crucial for predicting treatment outcomes.
- Children with dyskinetic CP often have less predictable responses to standard interventions.
Purpose of the Study:
- To objectively assess significant dyskinesia in children with CP using computer-based gait analysis.
- To identify distinct gait parameters associated with dyskinetic CP.
- To develop a predictive model for dyskinesia in children with CP.
Main Methods:
- Three-dimensional gait analysis was conducted on three groups: normal children, children with spastic CP, and children with dyskinetic CP.
- Participants were prospectively classified into spastic or dyskinetic groups based on clinical assessment.
- Statistical analysis included mixed model analysis of variance and logistic regression.
Main Results:
- Children with dyskinetic CP exhibited a significantly wider and more variable normalized dynamic base of support compared to spastic and normal groups.
- A smaller step profile (step length/step width) and greater, more variable maximal lateral acceleration were observed in the dyskinetic CP group.
- A predictive model using gait parameters achieved 87% sensitivity in classifying dyskinetic CP.
Conclusions:
- Children with dyskinetic cerebral palsy demonstrate unique and identifiable gait parameters.
- Computer-based gait analysis offers a viable method for objective dyskinesia assessment in children with CP.
- Objective gait parameter analysis can aid in the clinical classification and management of cerebral palsy.
Abstract:
The clinical classification of children with cerebral palsy is limited by multiple factors. Distinguishing between spasticity and dyskinesia is critical, because the outcome after standard orthopaedic and neurosurgical interventions is less predictable in children with cerebral palsy who have a significant dyskinetic component. This study applied computer-based analysis of gait to assess objectively the presence of significant dyskinesia in children with cerebral palsy. Three-dimensional gait analysis was performed on 18 normal children, 17 children with principally spastic cerebral palsy, and 23 children with significantly dyskinetic cerebral palsy. Children were assigned to the spastic or dyskinetic groups prospectively, based on clinical analysis by an experienced physician and physical therapist. The children with dyskinesia were found to have a significantly wider, and more variable normalized dynamic base of support, a smaller step profile (step length divided by step width), and a greater and more variable maximal lateral acceleration than the spastic and normal groups (mixed model analysis of variance, p = 0.0001). A predictive model of dyskinesia, (developed by logistic regression analysis), using these gait parameters, exhibited excellent sensitivity, correctly classifying 20 (87%) of 23 children as dyskinetic. This study shows that children with dyskinetic cerebral palsy have distinct gait parameters and that objective assessment of dyskinesia in children with cerebral palsy is possible with computer-based analysis of gait.