104 results match your criteria: "Hiroshima Cosmopolitan University[Affiliation]"

Article Synopsis
  • The study investigates which stroke patients benefit most from robot-assisted upper limb rehabilitation, specifically using the hybrid assistive limb (HAL-SJ) technology.
  • Using a machine learning method called the CHAID model, researchers identified key factors like age, sex, and cognitive function that predict a patient's improvement in upper limb function after therapy.
  • Results showed that the initial Fugl-Meyer Upper Extremity Evaluation score was the best predictor of improvement, with the model achieving high accuracy, suggesting early intervention in patients with moderate dysfunction leads to better outcomes.
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Distinctive MicroRNA Profiles in Serum of Patients with Neurofibromatosis Type 2: A Bioinformatic Exploratory Study.

World Neurosurg

August 2022

Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.

Objective: The objective of this study was to explore serum microRNA (miRNA) profile characteristic of patients with neurofibromatosis type 2 (NF2), including both sporadic and familial cases, by comprehensive analysis of miRNA expression using next-generation sequencing.

Methods: Nine patients with NF2 were included in this study. In addition, 7 patients with unilateral acoustic neuroma without a family history of NF2 were invited to participate as the control cohort in the study.

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

Front Neurorobot

March 2022

Department of Musculoskeletal Functional Research and Regeneration, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.

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.

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Article Synopsis
  • The study investigates the impact of different frequencies of using the single-joint hybrid assistive limb (HAL-SJ) on recovery of upper limb motor function and daily living activities in stroke patients.
  • Patients were divided into high and low frequency use groups, and improvements were assessed after 30 days, showing that high-frequency users had better results in specific motor functions and daily living assessments.
  • However, frequent use of the HAL-SJ didn’t significantly increase the number of patients achieving clinically meaningful improvements, suggesting that while frequency may aid recovery, it doesn't guarantee better outcomes for everyone.
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Objectives: To develop a clinical prediction rule (CPR) for gait independence at discharge in patients with stroke, using the decision-tree algorithm and to investigate the usefulness of CPR at admission to the rehabilitation ward.

Materials And Methods: We included 181 subjects with stroke during the postacute phase. The Chi-squared automatic interaction detection analysis method with 10-fold cross-validation was used to develop two CPRs; CPR 1 using easily obtainable data available at admission; CPR 2 using easily obtainable data available 1 month after admission, for prediction of gait independence at discharge.

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[Anti-doping from the Perspective of a Pharmacist and an Athlete].

Yakugaku Zasshi

February 2022

Hiroshima Dragonfly Co., Ltd.

I have been active as a professional basketball player at Hiroshima Dragonflies, which belongs to B.LEAGUE until 2018. At the beginning of my professional career, I started by balancing a pharmaceutical student and a professional life.

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Purpose: Gait changes are more prominently observed in older adults than in young adults, especially in kinematics of lower extremities and trunk. These changes can result in incidental falls during gait, possibly leading to inability to perform activities of daily living independently. This study aimed to investigate the effect of gender and age on gait changes, such as spatiotemporal parameters and peak joint angles in lower extremities and trunk during gait.

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Combining transcranial direct current stimulation (tDCS) and repetitive gait training may be effective for gait performance recovery after stroke; however, the timing of stimulation to obtain the best outcomes remains unclear. We performed a systematic review and meta-analysis to establish evidence for changes in gait performance between online stimulation (tDCS and repetitive gait training simultaneously) and offline stimulation (gait training after tDCS). We comprehensively searched the electronic databases Medline, Cochrane Central Register of Controlled Trials, Physiotherapy Evidence Database, and Cumulative Index to Nursing and Allied Health Literature, and included studies that combined cases of anodal tDCS with motor-related areas of the lower limbs and gait training.

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Development of a clinical prediction rule for patients with cervical spinal cord injury who have difficulty in obtaining independent living.

Spine J

February 2022

Graduate School of Humanities and Social Sciences, Hiroshima University, 1-3-2, Kagamiyama, Higashihiroshima 739-8511, Japan.

Background Context: A simple and easy to use clinical prediction rule (CPR) to detect patients with a cervical spinal cord injury (SCI) who would have difficulty in obtaining independent living status is vital for providing the optimal rehabilitation and education in both care recipients and caregivers. A machine learning approach was recently applied to the field of rehabilitation and has the possibility to develop an accurate and useful CPR.

Purpose: The aim of this study was to develop and assess a CPR using a decision tree algorithm for predicting which patients with a cervical SCI would have difficulty in obtaining an independent living.

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Article Synopsis
  • The study aimed to assess the effectiveness of five supervised machine learning algorithms in predicting the possibility of home discharge for stroke patients based on a dataset of 481 individuals.
  • The algorithms evaluated included decision tree, linear discriminant analysis, k-nearest neighbors, support vector machine, and random forest, measured by classification accuracy, area under the curve (AUC), and F1 score.
  • Results indicated that the k-NN model had the highest classification accuracy (84.0%), while the SVM model excelled in AUC and sensitivity, with both models showing promise for predicting home discharge outcomes.
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Article Synopsis
  • The effectiveness of MRI in predicting gait ability in stroke patients is still uncertain and has not been standardized in rehabilitation practices.
  • A systematic review of 19 studies found that damage to motor-related brain areas and the integrity of specific neural pathways are linked to gait recovery in stroke patients.
  • While MRIs show promise in predicting gait ability, the overall predictive value remains inconclusive due to concerns about study biases and a lack of quantitative evaluations.
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Article Synopsis
  • The study investigates how physical environmental factors impact the home discharge of stroke patients who use wheelchairs, suggesting that these factors are often overlooked.
  • The researchers utilized machine learning, specifically the CHAID algorithm, to analyze data from stroke patients in rehabilitation, aiming to identify what influences successful home discharge.
  • Key findings showed that house renovations and the presence of sloping roads are significant factors that impact whether wheelchair users can be discharged to home, highlighting the need for clinicians to consider these environmental elements in their assessments.
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Article Synopsis
  • The study aimed to explore factors influencing the discharge of walkable patients from psychiatric long-term care facilities in Japan.
  • Researchers assessed 73 walkable patients over two years, noting key differences in age, length of stay, and physical test scores between those discharged and those who remained hospitalized.
  • The analysis found that age significantly predicts the likelihood of discharge, as it relates to both the decline in motor function and the availability of social support post-discharge.
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[Purpose] In Japan, the government issued a state of emergency due to the spread of COVID-19 in April 2020. In this study, we measured physical activity before and after the state of emergency, and assessed the factors that affected physical activity. [Participants and Methods] We included thirteen elderly people living in Hiroshima Prefecture, Japan, in the study.

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Association between long-term hospitalization for mental illness and locomotive syndrome.

J Orthop Sci

March 2022

Department of Orthopaedic Surgery, Faculty of Medicine, University of Miyazaki, 5200 Kihara Kiyotake, Miyazaki 889-1692, Japan.

Background: Patients in psychiatric care wards face serious problems in terms of declining physical function due to aging and long-term hospitalization. This study aimed to determine the current status of locomotive syndrome (LS) in long-term inpatients in psychiatric care wards and to clarify the factors associated with LS risk severity.

Methods: The study included 84 patients admitted to psychiatric care wards who underwent the LS stage test.

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[Purpose] To analyze changes in the level of satisfaction of new physical therapists with their profession over time and in the factors that affect their satisfaction, focusing on the impact of previous experiences and working conditions. [Participants and Methods] This longitudinal survey study administered a questionnaire to 585 physical therapists who participated in the newcomer orientation at Hiroshima Prefectural Physical Therapy Association from 2017 to 2019 as follows: 210 in 2017, 188 in 2018, and 187 in 2019. The responses to the questions regarding professional satisfaction and the factors that affect it were investigated.

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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.

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Objective: We focused on locomotive syndrome as a low physical function factor that may prevent patients with psychiatric disease from being discharged. The purpose of this study is to clarify the factors, including locomotive syndrome, that prevent discharge from psychiatric long-term care wards.

Method: We enrolled 74 patients who were admitted to psychiatric long-term care wards at three different hospitals in Japan.

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[Purpose] Patients with idiopathic pulmonary fibrosis (IPF) often develop remarkable exercise-induced hypoxemia and are hospitalized for management. The pre-discharge management of activities of daily living (ADL) should determine the amount of exercise-induced hypoxemia permitted during daily activities and inform concrete instructions based on these results. This clinical report aimed to promote 24-hour ambulatory oximetry monitoring in a patient with IPF to guide the pre-discharge management of ADL.

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Background And Purpose: In severe stroke patients, considerable concern should be given to toileting activity in rehabilitative support. Recently, the application of artificial intelligence, including machine learning (ML), has expanded into the stroke medical field, which could clarify the factors affecting toileting independence in severe stroke patients. This study aimed to identify the factors affecting toileting independence in severe stroke patients using ML.

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Background: Patients with post-stroke hemiparesis have poor postural stability; nevertheless, it is unclear whether vestibular rehabilitation affects gait performance after a stroke or not. We performed a systematic review of randomized controlled trials to investigate the effects of vestibular rehabilitation on gait performance in patients with post stroke.

Methods: The Medline, Cochrane Central Register of Controlled Trials, Physiotherapy Evidence Database, and Cumulative Index to Nursing and Allied Health Literature databases were comprehensively searched.

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Article Synopsis
  • The study focuses on creating clinical prediction rules (CPRs) using changeable variables to predict activities of daily living (ADL) dependence in stroke patients, as some factors like age are unchangeable.
  • A total of 1,125 stroke patients were analyzed through machine learning, specifically using the classification and regression tree (CART) method, which utilized Functional Independence Measure (FIM) subscores.
  • The CART model found that certain FIM transfer scores were the best indicators of ADL dependence, achieving an accuracy rate of 83%.
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Background: Identifying early stages of hypersensitivity pneumonitis (HP) is hampered by variable presentation, heterogeneous or undetected causal antigens and lack of gold-standard biomarkers. Krebs von den Lungen (KL)-6 is pathophysiological biomarker of alveolar epithelial damage. Pigeon fanciers, susceptible to HP, provide a model to investigate early HP.

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Spatial navigation ability is associated with the assessment of smoothness of driving during changing lanes in older drivers.

J Physiol Anthropol

August 2020

Department of Human Behavior Science of Occupational Therapy, Health Sciences Major, Graduate School of Biomedical & Health Sciences, Hiroshima University, 1-2-3 Minamiku Kasumi, Hiroshima City, Hiroshima Pref, 734-8551, Japan.

Background: Age-related changes affect driving ability, including the smoothness of driving. This operation requires the use of both allocentric strategies (based on world-centered representations) and egocentric strategies (based on self-centered representations); however, with age, a greater preference for egocentric strategies is evident when driving. Furthermore, an age-related decline occurs in both driving ability and spatial navigation.

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Baseline High-Resolution CT Findings Predict Acute Exacerbation of Idiopathic Pulmonary Fibrosis: German and Japanese Cohort Study.

J Clin Med

November 2019

Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551, Japan.

Acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) is a major cause of morbidity and death in IPF. However, sensitive predictive factors of AE-IPF have not been well-investigated. To investigate whether high-resolution computed tomographic (HRCT) abnormalities predict AE-IPF in independent ethnic cohorts, this study included 121 patients with IPF (54 German and 67 Japanese; mean age, 68.

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