Early Initiation of Exoskeletal Robotic Gait Training Improves Functional Outcomes in the Patients with Stroke: A Retrospective Observational Study.

INTRODUCTION: The effect of early initiation of gait training using hybrid assistive limb (HAL) remains unclear. This observational study aimed to investigate whether early initiation of gait training using HAL improves functional outcomes in patients with stroke. METHODS: We retrospectively analyzed patients with acute stroke admitted to our facility. HAL was used for exoskeletal robotic gait training. Study participants were median split into an early group and a late group based on the days from stroke onset to initiation of gait training using HAL. The functional outcomes, defined by the Brunnstrom recovery stage (BRS), modified Rankin Scale (mRS), and Functional Independence Measure (FIM) at discharge, were compared using propensity score-matched analysis. RESULTS: We performed a propensity score-matched analysis in 63 patients with stroke (31 from the early group and 32 from the late group), and 17 pairs were matched. There were no significant differences in discharge in the BRS of the upper limb and finger in the post-matched cohort. On the other hand, the BRS of the lower limb in the early group was significantly higher than that in the late group. In addition, the mRS, but not FIM scores, was significantly better in the early group than that in the late group. CONCLUSIONS: In conclusion, early initiation of gait training using HAL might improve the motor function of the paralyzed lower limb and disability in patients with stroke.

Clinical Prediction Rule for Identifying the Stroke Patients who will Obtain Clinically Important Improvement of Upper Limb Motor Function by Robot-Assisted Upper Limb.

BACKGROUND: The number of studies on the characteristics of patients with stroke who would benefit from robot-assisted upper limb rehabilitation is limited, and there are no clear criteria for determining which individuals should receive such treatment. The current study aimed to develop a clinical prediction rule using machine learning to identify the characteristics of patients with stroke who can the achieve minimal clinically important difference of the Fugl-Meyer Upper Extremity Evaluation (FMA-UE) after single-joint hybrid assistive limb (HAL-SJ) rehabilitation. METHODS: This study included 71 patients with subacute stroke who received HAL-SJ rehabilitation. The chi-square automatic interaction detector (CHAID) model was applied to predict improvement in upper limb motor function. Based the analysis using CHAID, age, sex, days from stroke onset to the initiation of HAL-SJ rehabilitation, and upper limb motor and cognitive functions were used as independent variables. Improvement in upper limb motor function was determined based on the minimal clinically important difference of the FMA-UE, which was used as a dependent variable. RESULTS: According to the CHAID model, the FMA-UE score during the initiation of HAL-SJ rehabilitation was the most significant predictive factor for patients who are likely to respond to the intervention. Interestingly, this therapy was more effective in patients with moderate upper limb motor dysfunction and early initiation of HAL-SJ rehabilitation. The accuracy of the CHAID model was 0.89 (95% confidence interval: 0.81-0.96). CONCLUSION: We developed a clinical prediction rule for identifying the characteristics of patients with stroke whose upper limb motor function can improve with HAL-SJ rehabilitation.

Machine Learning Algorithm Identifies the Importance of Environmental Factors for Hospital Discharge to Home of Stroke Patients using Wheelchair after Discharge.

BACKGROUND AND PURPOSE: Physical environmental factors are generally likely to become barriers for discharge to home of wheelchair users, compared with non-wheelchair users. However, the importance of environmental factors has not been investigated adequately. Application of machine learning technology might efficiently identify the most influential factors, although it is not easy to interpret and integrate various information including individual and environmental factors in clinical stroke rehabilitation. This study aimed to identify the influential factors affecting home discharge in the stroke patients who use a wheelchair after discharge by using machine learning technology. METHODS: This study used the rehabilitation database of our facility, which includes all stroke patients admitted into the convalescence rehabilitation ward. The chi-squared automatic interaction detection (CHAID) algorithm was used to develop a model to classify wheelchair-using stroke patients discharged to home or not-to-home. RESULTS: Among the variables, including basic information, motor functional factor, activities of daily living ability factor, and environmental factors, the CHAID model identified house renovation and the existence of sloping roads around the house as the first and second discriminators for home discharge. CONCLUSIONS: Our present results could scientifically clarify that the clinician need to focus on the physical environmental factors for achieving home discharge in the patients who use a wheelchair after discharge.

Decision Tree Algorithm Identifies Stroke Patients Likely Discharge Home After Rehabilitation Using Functional and Environmental Predictors.

BACKGROUND AND PURPOSE: The importance of environmental factors for stroke patients to achieve home discharge was not scientifically proven. There are limited studies on the application of the decision tree algorithm with various functional and environmental variables to identify stroke patients with a high possibility of home discharge. The present study aimed to identify the factors, including functional and environmental factors, affecting home discharge after stroke inpatient rehabilitation using the machine learning method. METHOD: This was a cohort study on data from the maintained database of all patients with stroke who were admitted to the convalescence rehabilitation ward of our facility. In total, 1125 stroke patients were investigated. We developed three classification and regression tree (CART) models to identify the possibility of home discharge after inpatient rehabilitation. RESULTS: Among three models, CART model incorporating basic information, functional factor, and environmental factor variables achieved the highest accuracy for identification of home discharge. This model identified FIM dressing of the upper body (score of ≤2 or >2) as the first single discriminator for home discharge. Performing house renovation was associated with a high possibility of home discharge even in patients with stroke who had a poor FIM score in the ability to dress the upper body (≤2) at admission into the convalescence rehabilitation ward. Interestingly, many patients who performed house renovation have achieved home discharge regardless of the degree of lower limb paralysis. CONCLUSION: We identified the influential factors for realizing home discharge using the decision tree algorithm, including environmental factors, in patients with convalescent stroke.

Comparison of Supervised Machine Learning Algorithms for Classifying of Home Discharge Possibility in Convalescent Stroke Patients: A Secondary Analysis.

OBJECTIVES: Classifying the possibility of home discharge is important during stroke rehabilitation to support decision-making. There have been several studies on supervised machine learning algorithms, but only a few have compared the performance of different algorithms based on the same dataset for the classification of home discharge possibility. Therefore, we aimed to evaluate five supervised machine learning algorithms for the classification of home discharge possibility in stroke patients. MATERIALS AND METHODS: This was a secondary analysis based on the data of 481 stroke patients from the database of our institution. Five models developed by supervised machine learning algorithms, including decision tree (DT), linear discriminant analysis (LDA), k-nearest neighbors (k-NN), support vector machine (SVM), and random forest (RF) were compared by constructing a classification system based on the same dataset. Several parameters including classification accuracy, area under the curve (AUC), and F1 score (a weighted average of precision and recall) were used for model evaluation. RESULTS: The k-NN model had the best classification accuracy (84.0%) with a moderate AUC (0.88) and F1 score (87.8). The SVM model also showed high classification accuracy (82.6%) along with the highest AUC (0.91), sensitivity (94.4), negative predictive value (87.5), and negative likelihood ratio (0.088). The DT, LDA, and RF models had high classification accuracies (≥ 79.9%) with moderate AUCs (≥ 0.84) and F1 scores (≥ 83.8). CONCLUSIONS: Regarding model performance, the k-NN and SVM seemed the best candidate algorithms for classifying the possibility of home discharge in stroke patients.

Development and Validation of Machine Learning-Based Prediction for Dependence in the Activities of Daily Living after Stroke Inpatient Rehabilitation: A Decision-Tree Analysis.

BACKGROUND AND PURPOSE: Accurate prediction using simple and changeable variables is clinically meaningful because some known-predictors, such as stroke severity and patients age cannot be modified with rehabilitative treatment. There are limited clinical prediction rules (CPRs) that have been established using only changeable variables to predict the activities of daily living (ADL) dependence of stroke patients. This study aimed to develop and assess the CPRs using machine learning-based methods to identify ADL dependence in stroke patients. METHODS: In total, 1125 stroke patients were investigated. We used a maintained database of all stroke patients who were admitted to the convalescence rehabilitation ward of our facility. The classification and regression tree (CART) methodology with only the FIM subscores was used to predict the ADL dependence. RESULTS: The CART method identified FIM transfer (bed, chair, and wheelchair) (score ≤ 4.0 or > 4.0) as the best single discriminator for ADL dependence. Among those with FIM transfer (bed, chair, and wheelchair) score > 4.0, the next best predictor was FIM bathing (score ≤ 2.0 or > 2.0). Among those with FIM transfer (bed, chair, and wheelchair) score ≤ 4.0, the next predictor was FIM transfer toilet (score ≤ 3 or > 3). The accuracy of the CART model was 0.830 (95% confidence interval, 0.804-0.856). CONCLUSION: Machine learning-based CPRs with moderate predictive ability for the identification of ADL dependence in the stroke patients were developed.

Effects of Exoskeletal Lower Limb Robot Training on the Activities of Daily Living in Stroke Patients: Retrospective Pre-Post Comparison Using Propensity Score Matched Analysis.

PURPOSE: There is limited evidence of gait training using newly developed exoskeletal lower limb robot called Hybrid Assistive Limb (HAL) on the function and ability to perform ADL in stroke patients. In clinical settings, we frequently find it challenging to conduct a randomized controlled trial; thus, a large-scale observational study using propensity score analysis methods is a feasible alternative. The present study aimed to determine whether exoskeletal lower limb robot training improved the ability to perform ADL in stroke patients. MATERIALS AND METHODS: Acute stroke patients who were admitted to our facility from April 2016 to March 2017 were evaluated in the conventional rehabilitation period (CRP) and those admitted from April 2017 to June 2019 were evaluated in the HAL rehabilitation period (HRP). We started a new gait rehabilitation program using HAL at the midpoint of these two periods. The functional outcomes or ADL ability outcomes of the patients in the CRP and the subsequent HRP were compared using propensity score matched analyses. RESULTS: Propensity score matching analysis was performed for 108 stroke patients (63 from the CRP and 45 from the HRP), and 36 pairs were matched. The ADL ability, defined by the FIM scores and FIM score change, was significantly higher in patients admitted during the HRP. In addition, more stroke patients obtained practical walking ability during hospitalization in the HRP. CONCLUSION: Gait training using HAL affects the ADL ability and obtaining of practical walking ability of stroke patients.

Combination of Exoskeletal Upper Limb Robot and Occupational Therapy Improve Activities of Daily Living Function in Acute Stroke Patients.

PURPOSE: Previous studies have suggested that upper limb rehabilitation using therapeutic robots improves motor function of stroke patients. However, the effect of upper limb robotic rehabilitation on improving functioning in activities of daily living (ADL) remains unclear. The present study aimed to determine whether upper limb rehabilitation using single joint Hybrid Assistive Limb (HAL-SJ) affects ADL function and the use of a hemiparetic arm in ADLs of acute stroke patients. MATERIALS AND METHODS: Twelve acute stroke patients participated in the study and were randomly divided into group A or group B. The patients in group A followed an A-B-A-B design and those in group B followed a B-A-B-A design. The patients received combination HAL-SJ and occupational therapy during A and conventional occupational therapy during B. RESULTS: Upper limb motor function and ADLs, in particular, dressing the upper body, were improved during combination HAL-SJ and occupational therapy. Interestingly, the use of a hemiparetic arm in daily life evaluated using the motor activity log was also significantly improved during A in group A. CONCLUSIONS: Combination HAL-SJ and occupational therapy affects ADL function and real use of a hemiparetic arm in the daily life of acute stroke patients.

Efficacy, safety and pharmacokinetics of tedizolid versus linezolid in patients with skin and soft tissue infections in Japan - Results of a randomised, multicentre phase 3 study.

The objective of this open-label, randomised (i.e. 2:1 ratio), Phase 3 study was to compare the efficacy and safety of tedizolid phosphate 200 mg, once-daily treatment with that of linezolid 600 mg, twice-daily treatment for 7-14 days in Japanese adult patients (N = 125) with skin and soft tissue infections (SSTIs) and/or for 7-21 days for those with SSTI-related bacteraemia, caused by confirmed or highly suspected methicillin-resistant Staphylococcus aureus (MRSA). Primary outcome was clinical cure rate at test-of-cure (TOC, in SSTI: 7-14 days, in bacteraemia: 4-6 weeks after end-of-therapy [EOT]) time point in the microbiologically evaluable MRSA (ME-MRSA) population (N = 39). Secondary endpoints were clinical and microbiological response rates at EOT. Safety parameters were evaluated in the safety analysis population up to follow up. Data analysis was descriptive in nature. Baseline characteristics of patients were similar between treatment groups. At TOC in the ME-MRSA population, clinical cure rate was similar in tedizolid phosphate (92.6%) and linezolid (88.9%) groups. At EOT, clinical cure (tedizolid phosphate: 93.1%, linezolid: 90.0%) and microbiological success (tedizolid phosphate: 93.1%, linezolid: 100.0%) rates were similar in the ME-MRSA population. Both treatments were well tolerated; overall treatment-emergent adverse events (TEAEs) in tedizolid phosphate (79.5%) and linezolid (75.6%) treatment groups were similar. Drug-related TEAEs were numerically lower with tedizolid phosphate versus linezolid (30.1%; 39.0%, respectively), as well as gastrointestinal (21.7%; 26.8%) and myelosuppression-related (2.4%; 22.0%) TEAEs. One death occurred in the linezolid group. Tedizolid phosphate may be an appropriate antibiotic for the treatment of SSTIs in Japanese adult patients. International clinical trial registration number: NCT01967225. Japanese clinical trial registration number: JapicCTI-132308.

Polymer-Derived Silicoboron Carbonitride Foams for CO2 Capture: From Design to Application as Scaffolds for the in Situ Growth of Metal-Organic Frameworks.

A template-assisted polymer-derived ceramic route is investigated for preparing a series of silicoboron carbonitride (Si/B/C/N) foams with a hierarchical pore size distribution and tailorable interconnected porosity. A boron-modified polycarbosilazane was selected to impregnate monolithic silica and carbonaceous templates and form after pyrolysis and template removal Si/B/C/N foams. By changing the hard template nature and controlling the quantity of polymer to be impregnated, controlled micropore/macropore distributions with mesoscopic cell windows are generated. Specific surface areas from 29 to 239 m(2) g(-1) and porosities from 51 to 77 % are achieved. These foams combine a low density with a thermal insulation and a relatively good thermostructural stability. Their particular structure allowed the in situ growth of metal-organic frameworks (MOFs) directly within the open-cell structure. MOFs offered a microporosity feature to the resulting Si/B/C/N@MOF composite foams that allowed increasing the specific surface area to provide CO2 uptake of 2.2 %.

Identifying the characteristics of patients with stroke who have difficulty benefiting from gait training with the hybrid assistive limb: a retrospective cohort study.

Robot-assisted gait training is effective for walking independence in stroke rehabilitation, the hybrid assistive limb (HAL) is an example. However, gait training with HAL may not be effective for everyone, and it is not clear who is not expected to benefit. Therefore, we aimed to identify the characteristics of stroke patients who have difficulty gaining benefits from gait training with HAL. We conducted a single-institutional retrospective cohort study. The participants were 82 stroke patients who had received gait training with HAL during hospitalization. The dependent variable was the functional ambulation category (FAC) that a measure of gait independence in stroke patients, and five independent [age, National Institutes of Health Stroke Scale, Brunnstrom recovery stage (BRS), days from stroke onset, and functional independence measure total score (cognitive items)] variables were selected from previous studies and analyzed by logistic regression analysis. We evaluated the validity of logistic regression analysis by using several indicators, such as the area under the curve (AUC), and a confusion matrix. Age, days from stroke onset to HAL initiation, and BRS were identified as factors that significantly influenced walking independence through gait training with HAL. The AUC was 0.86. Furthermore, after building a confusion matrix, the calculated binary accuracy, sensitivity (recall), and specificity were 0.80, 0.80, and 0.81, respectively, indicated high accuracy. Our findings confirmed that older age, greater degree of paralysis, and delayed initiation of HAL-assisted training after stroke onset were associated with increased likelihood of walking dependence upon hospital discharge.

Downshift of the Ni d band center over Ni nanoparticles in situ confined within an amorphous silicon nitride matrix.

Herein, nanocomposites made of Ni nanoparticles in situ distributed in an amorphous silicon nitride (Ni/a-Si3N4) matrix, on the one hand, and within an amorphous silicon dioxide (Ni/a-SiO2) matrix, on the other hand, were synthesized from the same Ni-modified polysilazane precursor. In both compounds, the Ni/Si atomic ratio (0.06-0.07), average Ni nanocrystallite size (7.0-7.6 nm) and micro/mesoporosity of the matrix were rigorously fixed. Hydrogen (H2)-temperature-programmed desorption (TPD) profile analysis revealed that the activation energy for H2 desorption at about 100-130 °C evaluated for the Ni/a-Si3N4 sample (47.4 kJ mol-1) was lower than that for the Ni/a-SiO2 sample (68.0 kJ mol-1). Mechanistic study with X-ray photoelectron spectroscopy (XPS) analysis and density functional theory (DFT) calculations revealed that, at Ni nanoparticle/matrix heterointerfaces, Ni becomes more covalently bonded to N atoms in the a-Si3N4 matrix compared to O atoms in the a-SiO2 matrix. Therefore, based on experimental and theoretical studies, we elucidated that nickel-nitrogen (Ni-N) interactions at the heterointerface lead to remarkable Ni d band broadening and downshifting of the d band center relative to those generated by Ni-oxygen (Ni-O) interactions at the heterointerface. This facilitates H2 desorption, as experimentally observed in the Ni/a-Si3N4 sample.

Does frequent use of an exoskeletal upper limb robot improve motor function in stroke patients?

PURPOSE: To determine how differences in frequency of the single-joint hybrid assistive limb (HAL-SJ) use affect the improvement of upper limb motor function and activities of daily living (ADL) in stroke patients. MATERIALS AND METHODS: Subacute stroke patients were divided into the high or low frequency of HAL-SJ use groups. The two groups were matched by propensity score, and the degree of changes 30 days after initiating HAL-SJ use was compared. A logistic regression analysis was performed to examine whether frequent use would increase the number of subjects experiencing the efficacy of more than the minimal clinically important difference (MCID) of Fugl-Meyer assessment (FMA). RESULTS: Twenty-five stroke patients were matched by propensity score, and nine pairs were matched. The high-frequency group showed a significantly superior increase to total FMA shoulder, elbow, forearm, and Barthel index compared with the low-frequency group. Logistic regression analysis revealed no significant associations between frequent use and MCID. CONCLUSIONS: The frequency of HAL-SJ use may affect the improvement of motor function and ADL ability of the upper limb with exception of the fingers and wrist. However, the frequency of intervention was not effective enough to further increase the number of subjects with clinically meaningful changes in upper limb motor function.IMPLICATIONS FOR REHABILITATIONThe current study aimed to clarify how differences in the frequency of single-joint hybrid assistive limb (HAL-SJ) use can affect the improvement of upper-limb motor functions and ADL in subacute stroke patients.Our results implied that the frequency of HAL-SJ use may influence the recovery of upper limb function.However, even if HAL-SJ is used frequently, it does not mean that more patients will achieve clinically meaningful recovery.

Low temperature in situ immobilization of nanoscale fcc and hcp polymorphic nickel particles in polymer-derived Si-C-O-N(H) to promote electrocatalytic water oxidation in alkaline media.

We synthesized nickel (Ni) nanoparticles (NPs) in a high specific surface area (SSA) p-block element-containing inorganic compound prepared via the polymer-derived ceramics (PDC) route to dispatch the obtained nanocomposite towards oxygen evolution reaction (OER). The in situ formation of Ni NPs in an amorphous silicon carboxynitride (Si-C-O-N(H)) matrix is allowed by the reactive blending of a polysilazane, NiCl2 and DMF followed by the subsequent thermolysis of the Ni : organosilicon polymer coordination complex at a temperature as low as 500 °C in flowing argon. The final nanocomposite displays a BET SSA as high as 311 m2 g-1 while the structure of the NPs corresponds to face-centred cubic (fcc) Ni along with interstitial-atom free (IAF) hexagonal close-packed (hcp) Ni as revealed by XRD. A closer look into the compound through FEG-SEM microscopy confirms the formation of pure metallic Ni, while HR-TEM imaging reveals the occurrence of Ni particles featuring a fcc phase and surrounded by carbon layers; thus, forming core-shell structures, along with Ni NPs in an IAF hcp phase. By considering that this newly synthesized material contains only Ni without doping (e.g., Fe) with a low mass loading (0.15 mg cm-2), it shows promising OER performances with an overpotential as low as 360 mV at 10 mA cm-2 according to the high SSA matrix, the presence of the IAF hcp Ni NPs and the development of core-shell structures. Given the simplicity, the flexibility, and the low cost of the proposed synthesis approach, this work opens the doors towards a new family of very active and stable high SSA nanocomposites made by the PDC route containing well dispersed and accessible non-noble transition metals for electrocatalysis applications.

Effects of gait training with the Hybrid Assistive Limb on gait ability in stroke patients: A systematic review of randomized controlled trials.

The Hybrid Assistive Limb (HAL) is used in training to improve walking ability for stroke patients; however, the quality of the evidence for its effects has not been fully critiqued to date. This study conducted a systematic review of randomized controlled trials to investigate the effectiveness of post-stroke gait training with the HAL. PubMed, the Cochrane Library, the Physiotherapy Evidence Database (PEDro), and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) were searched for randomized controlled clinical trials evaluating the effect of HAL on gait training in stroke patients, published from the inception of each database until March 2021. Two authors screened the titles and abstracts of articles returned in the initial search and reviewed the full text of articles that met the selection criteria. The risk of bias was assessed using the PEDro scale. Of 273 articles retrieved from the databases, three met all inclusion criteria. One study showed that gait training using HAL improves independence in walking; however, the quality of this study was rated as 4 (medium quality). Other studies did not show improvement with HAL in walking independence. This review did not provide strong evidence to support the effectiveness of HAL in improving walking ability.

Mechanistic Investigation of the Formation of Nickel Nanocrystallites Embedded in Amorphous Silicon Nitride Nanocomposites.

Herein, we report the mechanistic investigation of the formation of nickel (Ni) nanocrystallites during the formation of amorphous silicon nitride at a temperature as low as 400 °C, using perhydropolysilazane (PHPS) as a preformed precursor and further coordinated by nickel chloride (NiCl2); thus, forming the non-noble transition metal (TM) as a potential catalyst and the support in an one-step process. It was demonstrated that NiCl2 catalyzed dehydrocoupling reactions between Si-H and N-H bonds in PHPS to afford ternary silylamino groups, which resulted in the formation of a nanocomposite precursor via complex formation: Ni(II) cation of NiCl2 coordinated the ternary silylamino ligands formed in situ. By monitoring intrinsic chemical reactions during the precursor pyrolysis under inert gas atmosphere, it was revealed that the Ni-N bond formed by a nucleophilic attack of the N atom on the Ni(II) cation center, followed by Ni nucleation below 300 °C, which was promoted by the decomposition of Ni nitride species. The latter was facilitated under the hydrogen-containing atmosphere generated by the NiCl2-catalyzed dehydrocoupling reaction. The increase of the temperature to 400 °C led to the formation of a covalently-bonded amorphous Si3N4 matrix surrounding Ni nanocrystallites.

Involvement of the Rostromedial Prefrontal Cortex in Human-Robot Interaction: fNIRS Evidence From a Robot-Assisted Motor Task.

Assistive exoskeleton robots are being widely applied in neurorehabilitation to improve upper-limb motor and somatosensory functions. During robot-assisted exercises, the central nervous system appears to highly attend to external information-processing (IP) to efficiently interact with robotic assistance. However, the neural mechanisms underlying this process remain unclear. The rostromedial prefrontal cortex (rmPFC) may be the core of the executive resource allocation that generates biases in the allocation of processing resources toward an external IP according to current behavioral demands. Here, we used functional near-infrared spectroscopy to investigate the cortical activation associated with executive resource allocation during a robot-assisted motor task. During data acquisition, participants performed a right-arm motor task using elbow flexion-extension movements in three different loading conditions: robotic assistive loading (ROB), resistive loading (RES), and non-loading (NON). Participants were asked to strive for kinematic consistency in their movements. A one-way repeated measures analysis of variance and general linear model-based methods were employed to examine task-related activity. We demonstrated that hemodynamic responses in the ventral and dorsal rmPFC were higher during ROB than during NON. Moreover, greater hemodynamic responses in the ventral rmPFC were observed during ROB than during RES. Increased activation in ventral and dorsal rmPFC subregions may be involved in the executive resource allocation that prioritizes external IP during human-robot interactions. In conclusion, these findings provide novel insights regarding the involvement of executive control during a robot-assisted motor task.

A systematic review of the usefulness of magnetic resonance imaging in predicting the gait ability of stroke patients.

The usefulness of magnetic resonance imaging (MRI) in predicting gait ability in stroke patients remains unclear. Therefore, MRI evaluations have not yet been standardized in stroke rehabilitation. We performed a systematic review to consolidate evidence regarding the use of MRIs in predicting gait ability of stroke patients. The Medline, Cumulative Index to Nursing and Allied Health Literature, and SCOPUS databases were comprehensively searched. We included all literature published from each source's earliest date to August 2020. We included 19 studies: 8 were classified as structure- or function-based MRI studies and 11 as neural tract integrity-based MRI studies. Most structure- or function-based MRI studies indicated that damage to motor-related areas (primary motor cortex, corona radiata, internal capsule, and basal ganglia) or insula was related to poor gait recovery. In neural tract integrity-based MRI studies, integrity of the corticospinal tract was related to gait ability. Some studies reported predictive value of the corticoreticular pathway. All included studies had some concerns, at least one, based on the Cochrane risk of bias instrument. This review suggests that MRIs are useful in predicting gait ability of stroke patients. However, we cannot make definitive conclusion regarding the predictive value, due to the lack of quantitative evaluations.

Relationship between Mobility-Related Activities of Daily Living and Health-Related Quality of Life among Healthy Older Adults: A Cross-Sectional Study Using Structural Equation Modeling.

Objective: To develop a conceptual model that confirms whether mobility-related activities of daily living (ADLs) abilities are strongly associated with reduced health-related quality of life (HRQOL) in older adults. Methods: A total of 153 participants (63 men, 90 women) were analyzed. The mobility-related ADL survey from the Ministry of Education, Culture, Sports, Science, and Technology of Japan was used. The Japanese version (v1.2) of the Medical Outcomes Study 36-item Short-Form Health Survey was administered to evaluate HRQOL. Structural equation modeling was performed to test a hypothetical model: mobility-related ADL abilities would influence HRQOL. Results: The chi-square value was not significant (chi-square = 9.463, p = .305), and goodness-of-fit values were high, implying that the model was validated; goodness-of-fit index, 0.981; adjusted goodness-of-fit index, 0.949; comparative fit index, 0.996; and root mean square error of approximation, 0.035. Results showed that mobility-related ADL abilities influenced the physical health including physical function and general health in HRQOL. Conclusions: This study developed the conceptual model confirming the influence of mobility-related ADL abilities especially on physical health. Further intervention studies on instructions/training for physical activity of healthy older adults should assess this causal relationship.

Reductions in Muscle Strength and Range of Motion Cause Locomotion Disability via Locomotion-Related Functional Limitation in Japanese Older Adults: A Cross-Sectional Study.

BACKGROUND: Functional issues (impairments, functional limitations, and disabilities) gradually occur with age. Nonetheless, maintaining physical capability may help prevent locomotion disabilities at an older age. The present study aimed to determine whether reductions in muscle strength and range of motion (ROM) cause locomotion disability via locomotion-related functional limitations among healthy older adults. METHODS: Data from a total of 144 participants (61 men, 83 women) were analyzed. To assess locomotion disability, the locomotor domain of the activities of daily living (ADLs) survey from the Ministry of Education, Culture, Sports, Science, and Technology of Japan was used. Muscle strength (grip strength) and two ROMs (hip flexion and knee flexion) were measured. To measure locomotion-related functional limitations, participants underwent a 10 m hurdle walking test and side-step test. Thereafter, path analysis was conducted for testing the hypothetical model. The goodness of fit in the model was assessed using statistical parameters, such as the chi-square value, goodness of fit index (GFI), adjusted goodness of fit index (AGFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA). RESULTS: The analysis revealed a nonsignificant chi-square value (chi-square = 41.885; p=0.113), as well as high values of GFI (0.944), AGFI (0.904), CFI (0.970), and RMSEA (0.046), indicating that locomotion disability was caused by locomotion-related functional limitations, which were influenced by muscle strength and ROM. CONCLUSIONS: The present study demonstrated that decreased muscle strength and ROM caused locomotion disability via locomotion-related functional limitations. Older adults should participate in physical exercise programs that focus on strengthening muscles and improving ROM to counteract age-related locomotion disability.