Robotic-assisted gait rehabilitation following stroke: a systematic review of current guidelines and practical clinical recommendations.

Abstract

INTRODUCTION\nStroke is the third leading cause of adult disability world-wide, and lower extremity motor impairment is one of the major determinants of long-term disability. Although robotic therapy is becoming more and more utilized in research protocols for lower limb stroke rehabilitation, the gap between research evidence and its use in clinical practice is still significant. The aim of this study was to determine the scope, quality, and consistency of guidelines for robotic lower limb rehabilitation after stroke, in order to provide clinical recommendations.\n\n\nEVIDENCE ACQUISITION\nWe systematically reviewed stroke rehabilitation guideline recommendations between January 1st, 2010 and October 31th, 2020. We explored electronic databases (n=4), guideline repositories and professional rehabilitation networks (n=12). Two independent reviewers used the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument, and brief syntheses were used to evaluate and compare the different recommendations, considering only the most recent version.\n\n\nEVIDENCE SYNTHESIS\nFrom the 1219 papers screened, ten eligible guidelines were identified from seven different regions/countries. Four of the included guidelines focused on stroke management, the other six on stroke rehabilitation. Robotic rehabilitation is generally recommended to improve lower limb motor function, including gait and strength. Unfortunately, there is still no consensus about the timing, frequency, training session duration and the exact characteristics of subjects who could benefit from robotics.\n\n\nCONCLUSIONS\nOur systematic review shows that the introduction of robotic rehabilitation in standard treatment protocols seems to be the future of stroke rehabilitation. However, robot assisted gait training (RAGT) for stroke needs to be improved with new solutions and in clinical practice guidelines, especially in terms of applicability.