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The state of the art is still lacking an extensive analysis of which clinical characteristics are leading to better outcomes after robot-assisted rehabilitation on post-stroke patients. Prognostic machine learning-based models could promote the identification of predictive factors and be exploited as Clinical Decision Support Systems (CDSS). For this reason, the aim of this work was to set the first steps toward the development of a CDSS, by the development of machine learning models for the functional outcome prediction of post-stroke patients after upper-limb robotic rehabilitation. Four different regression algorithms were trained and cross-validated using a nested 5× 10-fold cross-validation. The performances of each model on the test set were provided through the Median Average Error (MAE) and interquartile range. Additionally, interpretability analyses were performed, to evaluate the contribution of the features to the prediction. The results on the two best performing models showed a MAE of 13.6 [13.4] and 13.3 [14.8] on the Modified Barthel Index score (MBI). The interpretability analyses highlighted the Fugl-Meyer Assessment, MBI, and age as the most relevant features for the prediction of the outcome. This work showed promising results in terms of outcome prognosis after robot-assisted treatment. Further research should be planned for the development, validation and translation into clinical practice of CDSS in rehabilitation. Clinical relevance - This work establishes the premises for the development of data-driven tools able to support the clinical decision for the selection and optimisation of the robotic rehabilitation treatment.

Background: Stroke represents the second preventable cause of death after cardiovascular disease and the third global cause of disability. In countries where national registries of the clinical quality of stroke care have been established, the publication and sharing of the collected data have led to an improvement in the quality of care and survival of patients. However, information on rehabilitation processes and outcomes is often lacking, and predictors of functional outcomes remain poorly explored. This paper describes a multicenter study protocol to implement a Stroke rehabilitation Registry, mainly based on a multidimensional assessment proposed by the Italian Society of Physical and Rehabilitation Medicine (PMIC2020), in a pilot Italian cohort of stroke survivors undergoing post-acute inpatient rehabilitation, to provide a systematic assessment of processes and outcomes and develop data-driven prediction models of functional outcomes. Methods: All patients with a diagnosis of ischemic or haemorrhagic stroke confirmed by clinical assessment, admitted to intensive rehabilitation units within 30 days from the acute event, aged 18+, and providing informed consent will be enrolled. Measures will be taken at admission (T0), at discharge (T1), and at follow-up, 3 months (T2) and 6 months (T3) after the stroke. Assessment variables include anamnestic data, clinical and nursing complexity information and measures of body structures and function, activity and participation (PMIC2020), rehabilitation interventions, adverse events and discharge data. The modified Barthel Index will be our primary outcome. In addition to classical biostatistical analysis, learning algorithms will be cross-validated to achieve data-driven prognosis prediction models. Conclusions: This study will test the feasibility of a stroke rehabilitation registry in the Italian health context and provide a systematic assessment of processes and outcomes for quality assessment and benchmarking. By the

BACKGROUND: Gait impairments are common disabling symptoms of Parkinson's disease (PD). Among the approaches for gait rehabilitation, interest in robotic devices has grown in recent years. However, the effectiveness compared to other interventions, the optimum amount of training, the type of device, and which patients might benefit most remains unclear. OBJECTIVE: To conduct a systematic review about the effects on gait of robot-assisted gait training (RAGT) in PD patients and to provide advice for clinical practice. METHODS: A search was performed on PubMed, Scopus, PEDro, Cochrane library, Web of science, and guideline databases, following PRISMA guidelines. We included English articles if they used a robotic system with details about the intervention, the parameters, and the outcome measures. We evaluated the level and quality of evidence. RESULTS: We included twenty papers out of 230 results: two systematic reviews, 9 randomized controlled trials, 4 uncontrolled studies, and 5 descriptive reports. Nine studies used an exoskeleton device and the remainders end-effector robots, with large variability in terms of subjects' disease-related disability. CONCLUSIONS: RAGT showed benefits on gait and no adverse events were recorded. However, it does not seem superior to other interventions, except in patients with more severe symptoms and advanced disease.

BACKGROUND: Many robots are available for gait rehabilitation (BWSTRT and ORET) and their application in persons with SCI allowed an improvement of walking function.OBJECTIVE: The aim of the study is to compare the effects of different robotic exoskeletons gait training in persons with different SCI level and severity.METHODS: Sixty-two studies were included in this systematic review; the study quality was assessed according to GRADE and PEDro's scale.RESULTS: Quality assessment of included studies (n = 62) demonstrated a prevalence of evidence level 2; the quality of the studies was higher for BWSTRT (excellent and good) than for ORET (fair and good). Almost all persons recruited for BWSTRT had an incomplete SCI; both complete and incomplete SCI were recruited for ORET. The SCI lesion level in the persons recruited for BWSTRT are from cervical to sacral; mainly from thoracic to sacral for ORET; a high representation of AIS D lesion resulted both for BWSTRT (30%) and for ORET (45%). The walking performance, tested with 10MWT, 6MWT, TUG and WISCI, improved after exoskeleton training in persons with incomplete SCI lesions, when at least 20 sessions were applied. Persons with complete SCI lesions improved the dexterity in walking with exoskeleton, but did not recover independent walking function; symptoms such as spasticity, pain and cardiovascular endurance improved.CONCLUSION: Different exoskeletons are available for walking rehabilitation in persons with SCI. The choice about the kind of robotic gait training should be addressed on the basis of the lesion severity and the possible comorbidities.

Background: The recovery of walking after stroke is a priority goal for recovering autonomy. In the last years robotic systems employed for Robotic Assisted Gait Training (RAGT) were developed. However, literature and clinical practice did not offer standardized RAGT protocol or pattern of evaluation scales. Objective: This systematic review aimed to summarize the available evidence on the use of RAGT in post-stroke, following the CICERONE Consensus indications. Methods: The literature search was conducted on PubMed, Cochrane Library and PEDro, including studies with the following criteria: 1) adult post-stroke survivors with gait disability in acute/subacute/chronic phase; 2) RAGT as intervention; 3) any comparators; 4) outcome regarding impairment, activity, and participation; 5) both primary studies and reviews. Results: Sixty-one articles were selected. Data about characteristics of patients, level of disability, robotic devices used, RAGT protocols, outcome measures, and level of evidence were extracted. Conclusion: It is possible to identify robotic devices that are more suitable for specific phase disease and level of disability, but we identified significant variability in dose and protocols. RAGT as an add-on treatment seemed to be prevalent. Further studies are needed to investigate the outcomes achieved as a function of RAGT doses delivered.

Introduction: In recent years, robot-assisted gait training (raGt) has been proposed as therapy for balance and gait dysfunctions in people with multiple sclerosis (pwMs). through this systematic review, we aimed to discuss the impact of raGt on balance and gait outcomes. furthermore, characteristics of the training in terms of robots used, participants characteristics, protocols and combined therapeutic approaches have been described. EVidEncE acQuisition: as part of the italian consensus on robotic rehabilitation “cicEronE” a systematic search was provided in pubMed, the cochrane library and pEdro to identify relevant studies published before december 2019. only randomized control trials (rct) involving raGt for pwMs were included. pEdro scale was used to assess the risk of bias and the oxford center for Evidence-based Medicine (ocEbM) was used to assess level of evidence of included studies. EVIDENCE SYNTHESIS: The search on databases resulted in 336 records and, finally, 12 studies were included. RAGT was provided with Exoskeleton in ten studies (6-40 session, 2-5 per week) and with end-effector in two studies (12 sessions, 2-3 per week) with large variability in terms of participants’ disability. all the exoskeletons were combined with bodyweight support treadmill and movement assistance varied from 0% to 100% depending on participants’ disability, two studies combined exoskeleton with virtual reality. the end-effector speed ranged between 1.3 and 1.8 km/h, with bodyweight support starting from 50% and progressively reduced. in seven out of twelve studies raGt was provided in a multimodal rehabilitation program or in combination with standard physical therapy. there is level 2 evidence that raGt has positive impact in pwMs, reaching the minimally clinically importance difference in berg balance scale, six-minute walking test and gait speed. conclusions: in available rct, raGt is mostly provided with exoskeleton devices and improves balance and gait outcomes in

In this case series study, we aimed to evaluate the feasibility of a subacute rehabilitation program for mechanically ventilated patients with severe consequences of COVID-19 infection. Data were retrospectively collected from seven males (age 37-61 years) who were referred for inpatient rehabilitation following the stay in the ICU (14-22 days). On admission, six patients were still supported by mechanical ventilation. All patients were first placed in isolation in a special COVID unit for 6-22 days. Patients attended 11-24 treatment sessions for the duration of rehabilitation stay (13-27 days), including 6-20 sessions in the COVID unit. The treatment included pulmonary and physical rehabilitation. The initially nonventilated patient was discharged prematurely due to gallbladder problems, whereas all six mechanically ventilated patients were successfully weaned off before transfer to a COVID-free unit where they stayed for 7-19 days. At discharge, all patients increased limb muscle strength and thigh circumference, reduced activity-related dyspnea, regained functional independence and reported better quality of life. Rehabilitation plays a vital role in the recovery of seriously ill post-COVID-19 patients. Facilities should develop and implement plans for providing multidisciplinary rehabilitation treatments in various settings to recover functioning and prevent the development of long-term consequences of the COVID-19 disease.

Background and aims: Poststroke shoulder pain is a common complication. We aimed to investigate the prevalence of poststroke shoulder pain, with attention to the neuropathic component, and the relationship between poststroke shoulder pain and upper limb improvement in motor function, strength, disability, and quality of life after upper limb rehabilitation. Methods: This is a secondary analysis of a multicenter randomized controlled trial to compare upper limb conventional or robotic rehabilitation on 224 patients enrolled in eight rehabilitation centers. We assessed poststroke shoulder pain (using the Numerical Rating Scale and the Douleur Neuropathique 4), and upper limb motor function, strength, disability, and quality of life at baseline (T0), after 30 rehabilitation sessions (T1), and three months after the end of rehabilitation (T2). Results: A moderate/severe poststroke shoulder pain was reported by 28.9% of patients, while 19.6% of them showed a neuropathic component. At T0, the intensity of pain was higher in women and in patients with neglect syndrome, positively correlated with the time since stroke and disability and negatively correlated with motor function, strength, and the physical aspects of the quality of life. Moderate/severe pain and neuropathic component significantly reduced after both treatments and this reduction was maintained at T2. Finally, the intensity of pain at baseline was negatively correlated with the improvement of upper limb motor function. Conclusions: Poststroke shoulder pain negatively impact on motor performance, strength, disability, and physical aspects of the quality of life as well as on upper limb motor recovery; however, it can be reduced after a robotic or a conventional rehabilitation. Therefore, we suggest considering poststroke shoulder pain when planning the rehabilitation intervention.

Cognitive decline is often present in stroke survivors, with a significant impact on motor recovery. However, how specific cognitive domains could impact motor recovery after robotic rehabilitation in patients with stroke is still not well understood. In this study, we analyzed the relationship between cognitive impairment and the outcome of a robot-mediated upper limb rehabilitation intervention in a sample of 51 subacute stroke patients. Participants were enrolled and treated with a set of robotic and sensor-based devices. Before the intervention, patients underwent a cognitive assessment by means of the Oxford Cognitive Screen. To assess the effect of the 30-session rehabilitation intervention, patients were assessed twice with the following outcome measures: the Fugl-Meyer Assessment for Upper Extremity (FMA-UE), to evaluate motor function; the Upper limb Motricity Index (MI), to evaluate upper limb muscle strength; the Modified Barthel Index (mBI), to evaluate activities of daily living and mobility. We found that deficits in spatial attention and executive functions impacted the mBI improvement, while language, number processing, and spatial attention deficits reduced the gains in the FMA-UE. These results suggest the importance to evaluate the cognitive functions using an adequate tool in patients with stroke undergoing a robotic rehabilitation intervention.

Background: There is consistent evidence that robotic rehabilitation is at least as effective as conventional physiotherapy for upper extremity (UE) recovery after stroke, suggesting to focus research on which subgroups of patients may better respond to either intervention. In this study, we evaluated which baseline variables are associated with the response after the two approaches. Methods: This is a secondary analysis of a randomized-controlled trial comparing robotic and conventional treatment for the UE. After the assigned intervention, changes of the Fugl-Meyer Assessment UE score by ≥ 5 points classified patients as responders to treatment. Variables associated with the response were identified in a univariate analysis. Then, variables independently associated with recovery were investigated, in the whole group, and the two groups separately. Results: A sample of 190 patients was evaluated after the treatment; 121 were responders. Age, baseline impairment, and neglect were significantly associated with worse response to the treatment. Age was the only independently associated variable (OR 0.967, p = 0.023). Considering separately the two interventions, age remained negatively associated with recovery (OR 0.948, p = 0.013) in the conventional group, while none of the variables previously identified were significantly associated with the response to treatment in the robotic group. Conclusions: We found that, in our sample, age is significantly associated with the outcome after conventional but not robotic UE rehabilitation. Possible explanations may include an enhanced positive attitude of the older patients towards technological training and reduced age-associated fatigue provided by robotic-assisted exercise. The possibly higher challenge proposed by robotic training, unbiased by the negative stereotypes concerning very old patients’ expectations and chances to recover, may also explain our findings. Trial registration number: NCT02879279.

INTRODUCTION: There is growing evidence on the efficacy of gait robotic rehabilitation in patients with multiple sclerosis (MS), but most of the studies have focused on gait parameters. Moreover, clear indications on the clinical use of robotics still lack. As part of the CICERONE Italian Consensus on Robotic Rehabilitation, the aim of this systematic review was to investigate the existing evidence concerning the role of lower limb robotic rehabilitation in improving functional recovery in patients with MS. EVIDENCE ACQUISITION: We searched for and systematically reviewed evidence-based studies on gait robotic rehabilitation in MS, between January 1st, 2010 and December 31st, 2020, in the following databases: Cochrane Library, PEDro, PubMed and Google Scholar. The study quality was assessed by the 16-item assessment of multiple systematic reviews 2 (AMSTAR 2) and the 10-item PEDro scale for the other research studies. EVIDENCE SYNTHESIS: After an accurate screening, only 17 papers were included in the review, and most of them (13 RCT) had a level II evidence. Most of the studies used the Lokomat as a grounded robotic device, two investigated the efficacy of end-effectors and two powered exoskeletons. Generally speaking, robotic treatment has beneficial effects on gait speed, endurance and balance with comparable outcomes to those of conventional treatments. However, in more severe patients (EDSS >6), robotics leads to better functional outcomes. Notably, after gait training with robotics (especially when coupled to virtual reality) MS patients also reach better non-motor outcomes, including spasticity, fatigue, pain, psychological well-being and quality of life. Unfortunately, no clinical indications emerge on the treatment protocols. CONCLUSIONS: The present comprehensive systematic review highlights the potential beneficial role on functional outcomes of the lower limb robotic devices in people with MS. Future studies are warranted to evaluate the role of robot

Introduction: Stroke is the third leading cause of adult disability worldwide, 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. EVidEncE acQuisition: We systematically reviewed stroke rehabilitation guideline recommendations between January 1, 2010 and october 31, 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. EVIDENCE SYNTHESIS: From 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. conclusions: our 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.

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in coronavirus disease 2019 (COVID-19), has caused a pandemic. There is now considerable evidence that neuropsychological functions could be affected. We further tested this hypothesis on a sample of post COVID-19 patients, who, initially, had been severely affected.Methods We tested 22 post COVID-19 patients who, after the intensive care unit (all but one), were admitted to our rehabilitation unit to be treated for severe post COVID-19 sequelae. All patients were administered a comprehensive neuropsychological battery including measures assessing perceptual, attentive, mnestic, linguistic, and executive functions, and overall cognitive status. The patients were also administered rehabilitation measures including scales for investigating aerobic capacity/endurance deficits, dyspnea, and fatigue.Results Our findings revealed that evidence of neuropsychological disorders in post COVID-19 patients was very limited. Furthermore, COVID-19 severity and other relevant variables were not correlated with patients' scores on the neuropsy-chological tests.Conclusions We suggest that the relation between COVID-19 and neuropsychological disorders is unclear. New studies and metanalyses are highly required to shed light on this highly complex issue.

Details of the Clinical Case: A 51-yr-old man underwent a respiratory rehabilitation program (RRP), after being tracheostomized and ventilated due to acute respiratory distress syndrome (ARDS) from coronavirus disease-2019 (COVID-19) infection. Respiratory care, early mobilization, and neuromuscular electrical stimulation were started in the ad hoc isolation ward of our rehabilitation center. At baseline, muscle function was consistent with intensive care unit-acquired weakness and the patient still needed mechanical ventilation (MV) and oxygen support. During the first week of RRP in isolation, the patient was successfully weaned from MV, the tracheal cannula was removed, and the walking capacity was recovered. At the end of the RRP, continued in a standard department, respiratory muscles strength increased by 7% and muscle function improved as indicated by the quadriceps size enlargement of 13% and the change of the Medical Research Council sum score from 48/60 to 58/60. Discussion: Providing RRP in patients with severe COVID-19 ARDS involves risks for operators and organizational difficulties, especially in rehabilitation centers; nevertheless, its continuity is important to prevent the development of permanent disabilities in previously healthy subjects. Limited to the experience of only one patient, we were able to carry out a safe RRP during the COVID-19 pandemic, promoting the complete functional recovery of a COVID-19 young patient. Summary: Most patients who develop serious consequences of COVID-19 infection risk a reduction in their quality of life. However, by organizing and directing specialized resources, subacute rehabilitation facilities could ensure the continuity of the RRPs even during the COVID-19 pandemic.

Background and purpose: Rehabilitation plays a central role in stroke recovery. Besides conventional therapy, technological treatments have become available. The effectiveness and appropriateness of technological rehabilitation are not yet well defined; hence, research focused on different variables impacting recovery is needed. Results from the literature identified cognitive reserve (CR) as a variable impacting on the cognitive outcome. In this paper, the aim was to evaluate whether CR influences the motor outcome in patients after stroke treated with conventional or robotic therapy and whether it may influence one treatment rather than another. Methods: Seventy-five stroke patients were enrolled in five Italian neurological rehabilitation centres. Patients were assigned either to a robotic group, rehabilitation by means of robotic devices, or to a conventional group, where a traditional approach was used. Patients were evaluated at baseline and after rehabilitation treatment of 6 weeks through the Action Research Arm Test (ARAT), the Motricity Index (MI) and the Barthel Index (BI). CR was assessed at baseline using the Cognitive Reserve Index (CRI) questionnaire. Results: Considering all patients, a weak correlation was found between the CRI related to leisure time and MI evolution (r = 0.276; P = 0.02). Amongst the patients who performed a robotic rehabilitation, a moderate correlation emerged between the CRI related to working activities and MI evolution (r = 0.422; P = 0.02). Conclusions: Our results suggest that CR may influence the motor outcome. For each patient, CR and its subcategories should be considered in the choice between conventional and robotic treatment.

Background and Purpose: After stroke, only 12% of survivors obtain complete upper limb (UL) functional recovery, while in 30% to 60% UL deficits persist. Despite the complexity of the UL, prior robot-mediated therapy research has used only one robot in comparisons to conventional therapy. We evaluated the efficacy of robotic UL treatment using a set of 4 devices, compared with conventional therapy. Methods: In a multicenter, randomized controlled trial, 247 subjects with subacute stroke were assigned either to robotic (using a set of 4 devices) or to conventional treatment, each consisting of 30 sessions. Subjects were evaluated before and after treatment, with follow-up assessment after 3 months. The primary outcome measure was change from baseline in the Fugl-Meyer Assessment (FMA) score. Secondary outcome measures were selected to assess motor function, activities, and participation. Results: One hundred ninety subjects completed the posttreatment assessment, with a subset (n = 122) returning for follow-up evaluation. Mean FMA score improvement in the robotic group was 8.50 (confidence interval: 6.82 to 10.17), versus 8.57 (confidence interval: 6.97 to 10.18) in the conventional group, with no significant between-groups difference (adjusted mean difference-0.08, P = 0.948). Both groups also had similar change in secondary measures, except for the Motricity Index, with better results for the robotic group (adjusted mean difference 4.42, P = 0.037). At follow-up, subjects continued to improve with no between-groups differences. Discussion and Conclusions: Robotic treatment using a set of 4 devices significantly improved UL motor function, activities, and participation in subjects with subacute stroke to the same extent as a similar amount of conventional therapy. Video Abstract is available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A291).

Background and purpose: After stroke, only 12% of survivors obtain complete upper limb (UL) functional recovery, while in 30% to 60% UL deficits persist. Despite the complexity of the UL, prior robot-mediated therapy research has used only one robot in comparisons to conventional therapy. We evaluated the efficacy of robotic UL treatment using a set of 4 devices, compared with conventional therapy. Methods: In a multicenter, randomized controlled trial, 247 subjects with subacute stroke were assigned either to robotic (using a set of 4 devices) or to conventional treatment, each consisting of 30 sessions. Subjects were evaluated before and after treatment, with follow-up assessment after 3 months. The primary outcome measure was change from baseline in the Fugl-Meyer Assessment (FMA) score. Secondary outcome measures were selected to assess motor function, activities, and participation. Results: One hundred ninety subjects completed the posttreatment assessment, with a subset (n = 122) returning for follow-up evaluation. Mean FMA score improvement in the robotic group was 8.50 (confidence interval: 6.82 to 10.17), versus 8.57 (confidence interval: 6.97 to 10.18) in the conventional group, with no significant between-groups difference (adjusted mean difference -0.08, P = 0.948). Both groups also had similar change in secondary measures, except for the Motricity Index, with better results for the robotic group (adjusted mean difference 4.42, P = 0.037). At follow-up, subjects continued to improve with no between-groups differences. Discussion and conclusions: Robotic treatment using a set of 4 devices significantly improved UL motor function, activities, and participation in subjects with subacute stroke to the same extent as a similar amount of conventional therapy. Video Abstract is available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A291).

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