Objective: To evaluate the association between outcomes, including affected extremity functions and activities of daily living (ADL), and fractional anisotropy (FA) derived from automated tractography incorporating age among patients after stroke. Methods: This study enrolled stroke patients, and diffusion-tensor imaging was conducted during the second week. Standardized automated tractography was utilized to compute FA values in the corticospinal tract (CST), the inferior fronto-occipital fasciculus (IFOF), and the superior longitudinal fasciculus (SLF). Outcome evaluations were performed at discharge from our affiliated rehabilitation facility. Extremity functions were assessed using the total scores of the motor component of the Stroke Impairment Assessment Set (SIAS-motor). Independence levels in ADL were appraised through the motor and cognition components of the Functional Independence Measure (FIM). For each outcome measure, multivariate regression analysis incorporated the FA values of the CST, the IFOF, and the SLF, along with age. Results: Forty-two patients were enrolled in the final analytical database. Among the four explanatory variables, the CST emerged as the most influential factor for SIAS-motor scores. Conversely, age proved to be the primary determinant for both the motor and cognition components of FIM, surpassing the impact of FA metrics, including the CST and the IFOF. Conclusion The key influencing factors exhibited significant variations based on the targeted outcome assessments. Clinicians should be aware of these differences when utilizing neuroimaging techniques to predict stroke outcomes.

Objective: To evaluate the association between outcomes, including affected extremity functions and activities of daily living (ADL), and fractional anisotropy (FA) derived from automated tractography incorporating age among patients after stroke. Methods: This study enrolled stroke patients, and diffusion-tensor imaging was conducted during the second week. Standardized automated tractography was utilized to compute FA values in the corticospinal tract (CST), the inferior fronto-occipital fasciculus (IFOF), and the superior longitudinal fasciculus (SLF). Outcome evaluations were performed at discharge from our affiliated rehabilitation facility. Extremity functions were assessed using the total scores of the motor component of the Stroke Impairment Assessment Set (SIAS-motor). Independence levels in ADL were appraised through the motor and cognition components of the Functional Independence Measure (FIM). For each outcome measure, multivariate regression analysis incorporated the FA values of the CST, the IFOF, and the SLF, along with age. Results: Forty-two patients were enrolled in the final analytical database. Among the four explanatory variables, the CST emerged as the most influential factor for SIAS-motor scores. Conversely, age proved to be the primary determinant for both the motor and cognition components of FIM, surpassing the impact of FA metrics, including the CST and the IFOF. Conclusion The key influencing factors exhibited significant variations based on the targeted outcome assessments. Clinicians should be aware of these differences when utilizing neuroimaging techniques to predict stroke outcomes.

Objective: To evaluate the association between outcomes, including affected extremity functions and activities of daily living (ADL), and fractional anisotropy (FA) derived from automated tractography incorporating age among patients after stroke. Methods: This study enrolled stroke patients, and diffusion-tensor imaging was conducted during the second week. Standardized automated tractography was utilized to compute FA values in the corticospinal tract (CST), the inferior fronto-occipital fasciculus (IFOF), and the superior longitudinal fasciculus (SLF). Outcome evaluations were performed at discharge from our affiliated rehabilitation facility. Extremity functions were assessed using the total scores of the motor component of the Stroke Impairment Assessment Set (SIAS-motor). Independence levels in ADL were appraised through the motor and cognition components of the Functional Independence Measure (FIM). For each outcome measure, multivariate regression analysis incorporated the FA values of the CST, the IFOF, and the SLF, along with age. Results: Forty-two patients were enrolled in the final analytical database. Among the four explanatory variables, the CST emerged as the most influential factor for SIAS-motor scores. Conversely, age proved to be the primary determinant for both the motor and cognition components of FIM, surpassing the impact of FA metrics, including the CST and the IFOF. Conclusion The key influencing factors exhibited significant variations based on the targeted outcome assessments. Clinicians should be aware of these differences when utilizing neuroimaging techniques to predict stroke outcomes.

Objective: This study aimed to clarify the factors influencing the discharge destination of stroke patients in a super-aged rural community in Japan, focusing on functional independence and sociodemographic factors.Patients and Methods: We enrolled patients recovering from stroke with supratentorial lesions who were admitted to our convalescent rehabilitation hospital. The motor components of the Functional Independence Measure (FIM-motor) were assessed for each patient at admission and discharge as explanatory variables. An increase in the FIM-motor scores during hospitalization was also recorded. Additionally, sociodemographic data such as sex, age, and clinical characteristics, such as type of stroke, history of stroke, days from stroke onset to transfer to our convalescent rehabilitation hospital, total duration of hospital stay including acute care, number of co-resident household members, living with a spouse, and number of children were collected. As target values, discharge outcomes were categorized into two groups: returning home and going to a nursing home. Logistic regression analysis was performed.Results: The study sample comprised 160 patients (mean age ± standard deviation, 74.80 ± 12.19 years). Of these, 114 were discharged to their homes, and 46 were transferred to nursing homes. The results of multivariate logistic regression analysis indicated that higher FIM-motor scores at discharge, greater number of co-resident household members, and living with one’s spouse were the most powerful predictors of a higher probability of returning home.Conclusion: This study demonstrated that functional independence levels and the number of co-resident household members were crucial factors in predicting the discharge destination of patients after stroke in a super-aged rural community in Japan. These findings imply that for older patients with lower functional independence, supportive social networks are essential for home discharge, offering clues for providing long-term healthcare in super-aged rural communities worldwide.

Objective: To develop a new prediction model by combining independence in eating and bladder management functions, and to assess its utility in an acute care setting. Methods: Patients with ischemic stroke who were admitted in our acute stroke care unit (n=250) were enrolled in this study. Functional Independence Measure (FIM) scores for eating and bladder management on the initial day of rehabilitative treatment (median, 3 days) were collected as predictive variables. These scores were divided into low (<5) and high (≥5) and categorized as values 0 and 1, respectively. From the simple summation of these two-level model values, we derived a three-level model that categorized the scores as values 0, 1, and 2. The FIM-motor scores at discharge (median, 14 days) were collected as outcome measurements. The three-level model was assessed by observing the distribution patterns of the outcome FIM-motor scores and logistic regression analyses. Results: The median outcome FIM-motor score was 19 (interquartile range [IQR],13.8–45.3) for the value 0 category (n=14), 66.5 (IQR, 59.5–81.8) for the value 1 category (n=16), and 84 (IQR, 77–89) for the value 2 category (n=95) in the three-level model. Data fitting by logistic regression for FIM-motor scores of 41.3 and 61.4 reached 50% probability of values 1 and 2, respectively. Conclusion Despite the simplicity of the three-level model, it may be useful for predicting outcomes of patients with ischemic stroke in acute care.

Objective: To develop a new prediction model by combining independence in eating and bladder management functions, and to assess its utility in an acute care setting. Methods: Patients with ischemic stroke who were admitted in our acute stroke care unit (n=250) were enrolled in this study. Functional Independence Measure (FIM) scores for eating and bladder management on the initial day of rehabilitative treatment (median, 3 days) were collected as predictive variables. These scores were divided into low (<5) and high (≥5) and categorized as values 0 and 1, respectively. From the simple summation of these two-level model values, we derived a three-level model that categorized the scores as values 0, 1, and 2. The FIM-motor scores at discharge (median, 14 days) were collected as outcome measurements. The three-level model was assessed by observing the distribution patterns of the outcome FIM-motor scores and logistic regression analyses. Results: The median outcome FIM-motor score was 19 (interquartile range [IQR],13.8–45.3) for the value 0 category (n=14), 66.5 (IQR, 59.5–81.8) for the value 1 category (n=16), and 84 (IQR, 77–89) for the value 2 category (n=95) in the three-level model. Data fitting by logistic regression for FIM-motor scores of 41.3 and 61.4 reached 50% probability of values 1 and 2, respectively. Conclusion Despite the simplicity of the three-level model, it may be useful for predicting outcomes of patients with ischemic stroke in acute care.

Objective：Brain disorders are major concerns in rehabilitation medicine in Japan. Of the various categories of brain disorders, rehabilitative treatments for strokes, traumatic brain injuries, and neurodegenerative diseases are different. This study aimed to demonstrate the specificities of the rehabilitative treatments for these three subcategories after statistical analysis of textual data from abstracts indexed during an annual meeting for rehabilitation medicine.Materials and Methods：Abstracts indexed during the 56th annual meeting of the Japanese Association of Rehabilitation Medicine in 2019 were entered into the analytical database. Words associated with each subcategory were extracted using Jaccard's similarity coefficients.Results：The analysies showed that the words strongly associated with strokes were “paresis,” “convalescent,” “admission,” “onset,” “ward,” “function,” “FIM,” “impairment,” “improvement,” and “discharge” (extracted from 402 abstracts；coefficients ranged from 0.36 to 0.23). In parallel, the words such as “trauma,” “traffic,” “higher,” “accident,” “fall,” “brain,” “labor,” “brain-disease,” “hematoma,” and “facility” were related to traumatic brain injuries (extracted from 36 abstracts；coefficients ranged from 0.15 to 0.08). The words strongly associated with neurodegenerative diseases were “cognition,” “MMSE,” “elderly,” “care,” “home,” “nursing home,” “fracture,” “impairment,” “Yahr,” and “disease” (extracted from 96 abstracts；coefficients ranged from 0.18 to 0.09).Conclusions：The specifics of rehabilitative treatments for strokes, traumatic brain injuries, and neurodegenerative diseases were successfully outlined after the analysies of the textual data. This technique may be useful for evaluating information provided in textual forms, such as abstracts of conferences.

Objective：Brain disorders are major concerns in rehabilitation medicine in Japan. Of the various categories of brain disorders, rehabilitative treatments for strokes, traumatic brain injuries, and neurodegenerative diseases are different. This study aimed to demonstrate the specificities of the rehabilitative treatments for these three subcategories after statistical analysis of textual data from abstracts indexed during an annual meeting for rehabilitation medicine.Materials and Methods：Abstracts indexed during the 56th annual meeting of the Japanese Association of Rehabilitation Medicine in 2019 were entered into the analytical database. Words associated with each subcategory were extracted using Jaccard's similarity coefficients.Results：The analysies showed that the words strongly associated with strokes were “paresis,” “convalescent,” “admission,” “onset,” “ward,” “function,” “FIM,” “impairment,” “improvement,” and “discharge” (extracted from 402 abstracts；coefficients ranged from 0.36 to 0.23). In parallel, the words such as “trauma,” “traffic,” “higher,” “accident,” “fall,” “brain,” “labor,” “brain-disease,” “hematoma,” and “facility” were related to traumatic brain injuries (extracted from 36 abstracts；coefficients ranged from 0.15 to 0.08). The words strongly associated with neurodegenerative diseases were “cognition,” “MMSE,” “elderly,” “care,” “home,” “nursing home,” “fracture,” “impairment,” “Yahr,” and “disease” (extracted from 96 abstracts；coefficients ranged from 0.18 to 0.09).Conclusions：The specifics of rehabilitative treatments for strokes, traumatic brain injuries, and neurodegenerative diseases were successfully outlined after the analysies of the textual data. This technique may be useful for evaluating information provided in textual forms, such as abstracts of conferences.