Predictors of functional and motor outcomes following upper limb robot-assisted therapy after stroke.

Abstract

Robot-assisted therapy is an effective treatment for stroke patients and has recently gained popularity. Clinicians and researchers are trying to identify predictors to stratify patients for ensuring better stroke rehabilitation outcomes. However, previous studies have reported controversial results regarding the predictors of upper limb recovery after robot-assisted therapy. Our objective was to determine whether the demographic and clinical characteristics of stroke patients influence the motor and functional outcomes after robot-assisted therapy. We conducted a retrospective analysis of 48 hemiplegic patients who performed upper limb goal-directed tasks using RAPAEL Smart Glove (Neofect, Gyeonggi-do, Republic of Korea). Robot-assisted therapy was administered for 5 days a week over 4 weeks, and each session was for 30 minutes. The parameters of the primary outcomes after robot-assisted therapy were measured with the manual function test and functional independence measure. Correlation analysis showed that age, initial cognitive function, and the initial manual function test and the Modified Ashworth Scale for upper extremity scores were significant factors for independently predicting functional outcomes after robot-assisted therapy. Linear regression analysis revealed that the initial Mini-Mental State Examination (P < 0.001) and initial manual function test (P < 0.001) scores were significant predictors of the primary outcomes. In conclusion, our study suggests that stroke patients presenting with less spasticity, better initial cognitive function, and better initial motor function have a significant correlation with the functional outcomes after robot-assisted therapy.