Multi-segmental Robotic and Technological Upper Limb Rehabilitation in Stroke

Overview

Stroke is frequently associated with significant disability and impaired quality of life. Persistent motor impairment is common with often incomplete recovery of motor function in response to rehabilitation, mainly in the upper limbs. Robot-mediated therapy has been proposed as a viable approach for the rehabilitation of the upper limb, but as the evidence quality is low, more rigorous studies are needed. Previous studies have focused on the effects of devices acting on a limited number of joints, often limiting the workspace on a plane. This study aims to evaluate the efficacy of a multi-set of robotic and technological devices for the rehabilitation of the upper limb in sub-acute stroke patients.

Stroke is the first cause of disability in the world, with a very high social impact. Recovery is partial in 85% of stroke survivors, 35% of whom have a persisting serious disability. The increase in lifespan is leading to a rise in the incidence of stroke, and therefore to a rise in the number of people requiring a rehabilitation program. Rehabilitation programs are mainly focused on walking recovery, with insufficient attention being paid to upper limb recovery. Thirty to 60% of patients treated with conventional therapy present functional deficits of the paretic arm, resulting in an impairment of activities of daily living. Robot-mediated therapy (RT) has been proposed in the literature as a viable approach for the rehabilitation of the upper limb. A first meta-analysis of 262 subjects showed that when the duration/intensity of conventional therapy (CT) is matched with that of the robot-assisted therapy, no difference exists between the two groups in terms of motor recovery, activities of daily living, strength or motor control; instead, when the RT is added to CT, a greater effectiveness can be observed, when compared with regular CT alone (5). A subsequent meta-analysis by Mehrholz et al., including 19 trials (involving 666 subjects), showed that RT was more effective than other interventions in improving patients' activities of daily living (SMD 0.43, 95% confidence interval (CI) 0.11 to 0.75, P = 0.009, I2 = 67%). In the same sample, stratified by time since disease onset, the analysis confirmed that RT was more effective in improving the activities of daily living in the 224 acute and sub-acute patients (within 3 months of stroke onset) (SMD 0.64, 95% CI 0.14 to 1.15, P=0.01, I2 =69%). The same findings were not confirmed in 334 chronic patients (more than 3 months after stroke) (SMD 0.85, 95% CI -0.27 to 1.97, P=0.14, I2 =94%). As for the other outcomes, robotic therapy was more effective in improving upper extremity function (SMD 0.45, 95% CI 0.20 to 0.69, P = 0.0004, I2 = 45%), but not muscular strength (SMD 0.48, 95% CI -0.06 to 1.03, P = 0.08, I2 = 79%). Finally, RT was well accepted by patients, there was no marked increase in the number of drop-outs, and serious adverse events were rare and unrelated to the robotic treatment (6). In an update of their meta-analysis, published in 2015, the same research team confirmed that RT was more effective than other therapies in improving activities of daily living (SMD 0.37, 95% confidence interval (CI) 0.11 to 0.64, P = 0.005, I² = 62%), motor function (SMD 0.35, 95% CI 0.18 to 0.51, P \< 0.0001, I² = 36%) and strength (SMD 0.36, 95% CI 0.01 to 0.70, P = 0.04, I² = 72%) of the upper limb. RT was well accepted by patients, there was no marked increase in the number of drop-outs (RD 0.00, 95% CI -0.02 to 0.03, P = 0.84, I² = 0%), and serious adverse events were rare and unrelated to the robotic treatment. However, the authors concluded that the evidence quality was low, highlighting the need for more rigorous studies. It should be noted that the authors of the review highlighted the fact that the studies reviewed were heterogeneous in terms of study design (two arms, four arms, parallel groups or cross-over, duration of follow-up and selection criteria), of the devices used for the therapeutic treatment, of the patients' characteristics (time since disease onset), of the methodological protocols (methods of randomization, of the blindness of the outcome assessors to group allocation, and of the presence or absence of an intention to treat analysis). However, the authors emphasized that limitations such as the inability to blind the therapist and participants, i.e. the so-called contamination (provision of the intervention to the control group), and co-intervention (when the same therapist unintentionally provides additional care to either treatment or comparison group) has often been present in rehabilitation studies. Moreover, they pointed out that sometimes the sample is selected according to comorbidities, age, spasticity or pain; instead, in clinical practice patients are often older, and the prevalence of comorbidity, pain, spasticity and/or limitations of articular function is higher than that reported in the studies analyzed. Therefore, inclusion criteria that allow the effects of a robotic treatment to be evaluated on a larger sample of patients with stroke, with clinical characteristics as close as possible to the real-world clinical setting, are desirable. Many authors have highlighted the impact on costs and the greater sustainability of the RT when compared with the CT. The latter requires a ratio of one therapist to one patient, while RT, after adequate training of the therapist, allows a ratio of one therapist to every three or four patients, depending on the technology used. RT allows patients' improvements to be assessed even after a single treatment session, to constantly monitor the rehabilitation program and therefore to better define the best rehabilitation strategies. In fact, thanks to the possibility the systems available, it is possible to customize the treatment based on the patients' clinical characteristics. Last but not least, robotic devices involve and motivate patients, providing them with visual and auditory feedback through virtual reality programs in the form of games. Training progresses through increasingly difficult stages that can be linked by patients to their own progress. This becomes an important stimulus to increase the active participation of patients in the rehabilitation program. Almost all scientific papers in the literature have focused on the effects of the use of one or, at most, two robotic devices, compared with a conventional approach. However, even though the anatomy and the motor function of the upper limbs, especially the hand, is extremely complex, all but a very few commercial devices act on a limited number of joints and limit the workspace on a plane. By contrast, during conventional therapy the whole upper limb is routinely treated and the three-dimensional space, in which the upper limb is normally required to move to accomplish daily activities, is normally explored. In the light of the above, it is very difficult to compare the effects of robotic and traditional approaches. This results in the need for a multi-set of robots and electromechanical systems, each of which acts on a different joint and/or on a different plane, in upper limb rehabilitation in stroke patients. To the best of our knowledge, the effects of a similar approach, i.e. the use of a multi-set of robotic devices to restore motor function in patients with stroke, have never been compared with those of a conventional approach. Moreover, the effects should ideally be explored on a large sample of subjects that are representative of clinical practice. Hypothesis. The rationale behind the study is that a multi-set of robotic devices used to treat the whole upper limb may be more effective than conventional treatments in improving upper limb motor performance, since they raise the degree of motivation and participation among patients, and provide a more intensive, standardized and individualized treatment. Therefore, the investigators wish to verify this hypothesis on a large sample of subjects, within a multicenter study using the same multi-set of robotic devices and the same outcome measures, to obtain better-quality scientific evidence than that currently available in the literature. Aim: to assess, using evidence-based criteria (RCT), the effectiveness of a rehabilitation program targeting all the upper limb joints in stroke patients, using a multi-set of robotic and technological systems, by comparing it with that of a conventional approach.