The PREP algorithm predicts potential for upper limb recovery after stroke

Abstract

Stroke is a leading cause of adult disability and the recovery of motor function is important for independence in activities of daily living. Predicting motor recovery after stroke in individual patients is difficult. Accurate prognosis would enable realistic rehabilitation goal-setting and more efficient allocation of resources. The aim of this study was to test and refine an algorithm for predicting the potential for recovery of upper limb function after stroke. Forty participants were prospectively enrolled within 3 days of ischaemic stroke. First, shoulder abduction and finger extension strength were graded 72 h after stroke onset to compute a shoulder abduction and finger extension score. Secondly, transcranial magnetic stimulation was used to assess the functional integrity of descending motor pathways to the affected upper limb. Third, diffusion-weighted magnetic resonance imaging was used to assess the structural integrity of the posterior limbs of the internal capsules. Finally, these measures were combined in the PREP algorithm for predicting an individual's potential for upper limb recovery at 12 weeks, measured with the Action Research Arm Test. A cluster analysis was used to independently group patients according to Action Research Arm Test score at 12 weeks, for comparison with predictions from the PREP algorithm. There was excellent correspondence between the cluster analysis of Action Research Arm Test score at 12 weeks and predictions made with the PREP algorithm. The algorithm had positive predictive power of 88%, negative predictive power of 83%, specificity of 88% and sensitivity of 73%. This study provides preliminary data in support of the PREP algorithm for the prognosis of upper limb recovery in individual patients. PREP may enable tailored planning of rehabilitation and more accurate stratification of patients in clinical trials.