Adopting Literature-based Discovery on Rehabilitation Therapy Repositioning for Stroke

Stroke is a common disabling disease severely affecting the daily life of the patients. There is evidence that rehabilitation therapy can improve the movement function. However, there are no clear guidelines that identify specific, effective rehabilitation therapy schemes, and the development of new rehabilitation techniques has been fairly slow. One informatics translational approach, called ABC model in Literature-based Discovery, was used to mine an existing rehabilitation candidate which is most likely to be repositioned for stroke. As in the classic ABC model originated from Don Swanson, we built the internal links of stroke (A), assessment scales (B), rehabilitation therapies (C) in PubMed relating to upper limb function measurements for stroke patients. In the first step, with E-utility we retrieved both stroke related assessment scales and rehabilitation therapies records, and complied two datasets called Stroke_Scales and Stroke_Therapies, respectively. In the next step, we crawled all rehabilitation therapies co-occurred with the Stroke_Theapies, named as All_Therapies. Therapies that were already included in Stroke_Therapies were deleted from All_Therapies, so that the remaining therapies were the potential rehabilitation therapies, which could be repositioned for stroke after subsequent filtration by manual check. We identified the top ranked repositioning rehabilitation therapy following by subsequent clinical validation. Hand-arm bimanual intensive training (HABIT) ranked the first in our repositioning rehabilitation therapies list, with the most interaction links with Stroke_Scales. HABIT showed a significant improvement in clinical scores on assessment scales of Fugl-Meyer Assessment and Action Research Arm Test in the clinical validation on upper limb function for acute stroke patients. Based on the ABC model and clinical validation of the results, we put forward that HABIT as a promising rehabilitation therapy for stroke, which shows that the ABC model is an effective text mining approach for rehabilitation therapy repositioning. The results seem to be promoted in clinical knowledge discovery.


Publication Date:
Sep 19 2018
Date Submitted:
Jun 28 2019
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 Record created 2019-06-28, last modified 2019-07-11


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