Abstract
BackgroundAnkle-foot orthosis (AFO) prescriptions are common for patients diagnosed with cerebral palsy (CP). Typical treatment objectives are to improve ankle-foot function and enhance general gait quality. ObjectiveTo determine the effectiveness of AFOs for improving the gait of children with diplegic CP. DesignRetrospective analysis. SettingPrimary clinical care facility. ParticipantsData were used from 601 visits for 378 individuals (age at visit: 9.8 ± 3.8 years [mean ± standard deviation]) who wore either a solid, hinged, or posterior leaf spring AFO design. Participants had a diagnosis of diplegic CP, wore the same AFO design bilaterally, and had 3-dimensional gait analysis data collected while walking both barefoot and with AFOs during a single session. MethodsDifferences between walking with AFOs and walking barefoot were used as outcome measures. Statistical analysis consisted of paired t-tests and multivariate analysis of variance scores to determine significance, main effects, and interactions of AFO design, ambulation type (walking with/without assistive devices), and barefoot level on each outcome. Minimal clinically important differences from the literature determined clinical significance. Outcome MeasuresGait Deviation Index (GDI), ankle Gait Variable Score, knee Gait Variable Score, nondimensional speed, and nondimensional step length. ResultsOnly step length exhibited clinically meaningful improvements for the average AFO user. Changes in step length, speed, and GDI all were statistically significant (P < .001). Barefoot outcome levels were the most consistent influence on outcome changes. AFO design was shown to effect changes in speed and ankle function, whereas ambulation type was shown to affect GDI change. ConclusionsCurrent AFO prescription methodologies for children with CP result in consistent gait improvements for step length only. This study emphasizes the need to develop more effective AFO prescription algorithms in an effort to improve the efficacy of AFOs on general gait quality via optimizing patient selection or AFO design.
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