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Rationale Functional strength training in addition to conventional physical therapy could enhance upper limb recovery early after stroke more than movement performance therapy plus conventional physical therapy. Aims To determine (a) the relative clinical efficacy of conventional physical therapy combined with functional strength training and conventional physical therapy combined with movement performance therapy for upper limb recovery; (b) the neural correlates of response to conventional physical therapy combined with functional strength training and conventional physical therapy combined with movement performance therapy; (c) whether any one or combination of baseline measures predict motor improvement in response to conventional physical therapy combined with functional strength training or conventional physical therapy combined with movement performance therapy. Design Randomized, controlled, observer-blind trial. Study The sample will consist of 288 participants with upper limb paresis resulting from a stroke that occurred within the previous 60 days. All will be allocated to conventional physical therapy combined with functional strength training or conventional physical therapy combined with movement performance therapy. Functional strength training and movement performance therapy will be undertaken for up to 1·5 h/day, five-days/week for six-weeks. Outcomes and Analysis Measurements will be undertaken before randomization, six-weeks thereafter, and six-months after stroke. Primary efficacy outcome will be the Action Research Arm Test. Explanatory measurements will include voxel-wise estimates of brain activity during hand movement, brain white matter integrity (fractional anisotropy), and brain-muscle connectivity (e.g. latency of motor evoked potentials). The primary clinical efficacy analysis will compare treatment groups using a multilevel normal linear model adjusting for stratification variables and for which therapist administered the treatment. Effect of conventional physical therapy combined with functional strength training versus conventional physical therapy combined with movement performance therapy will be summarized using the adjusted mean difference and 95% confidence interval. To identify the neural correlates of improvement in both groups, we will investigate associations between change from baseline in clinical outcomes and each explanatory measure. To identify baseline measurements that independently predict motor improvement, we will develop a multiple regression model. [ABSTRACT FROM AUTHOR]

Rationale An ankle-foot cast may enable people to repeatedly practice walking with a more normal movement pattern early after stroke. Aims To evaluate the clinical efficacy of using an ankle-foot cast [soft scotch ankle-foot ( SWIFT) Cast] to enhance walking recovery and to find whether site of stroke lesion and/or baseline biomechanical characteristics predict response to a SWIFT Cast. Design Randomized, controlled, observer-blind trial. Study Participants ( n = 120), 3-42 days after stroke with walking difficulty. All will receive conventional physical therapy. Those allocated to the experimental group will also receive a SWIFT Cast for up to six-weeks. During therapy sessions, the SWIFT Cast will be worn for retraining of walking as clinically appropriate. Outside therapy sessions, participants will initially wear the SWIFT Cast for the whole of their waking day, and this will be adjusted as clinically appropriate. Outcomes Measures will be undertaken before randomization, six-weeks thereafter and six-months after stroke. Primary outcome will be walking speed. Secondary outcomes will include the Functional Ambulation Category and efficiency of gait (e.g. step-time symmetry). Structural brain imaging using magnetic resonance imaging (standard fluid attenuated inversion recovery and T1-weighted high-resolution 'volume' spoiled gradient) will be undertaken at baseline. The clinical efficacy analysis will use analysis of covariance. The relationship between clinical response to therapy and biomechanical data will use correlation and multivariate regression techniques as required. For neuroimaging data, the relationship to clinical response to therapy will be computed using voxel-based lesion-symptom mapping. An interaction test across groups will identify which voxels are associated with different mean levels of treatment efficacy. [ABSTRACT FROM AUTHOR]