Botulinum toxin type A (BTXA) has been shown to be an effective treatment in reducing muscle tone and managing spasticity in poststroke patients. However, its effectiveness in improving function in lower limb spasticity has been more controversial. In this report, we present our findings in three cases of chronic stroke patients with lower limb spasticity wherein we examine the effectiveness of a 4-week intensive rehabilitation program following BTXA treatment. For each patient, BTXA was injected into spastic muscles of the affected lower limb and a rehabilitation program was provided for the patient in-hospital for 4 weeks. Before BTXA treatment (baseline) and at 2 and 4 week follow-ups after each treatment, the Stroke Impairment Assessment Set (SIAS), the Modified Ashworth Scale (MAS) and the Range of Motion (ROM) of the ankle, the 10 Meter Walking Test (10MWT), the 6 minutes walking distance (6MD), the Timed Up and Go Test (TUG), the Berg Balance Scale (BBS), and the Functional Independence Measure (FIM) were all assessed. In each patient, ankle MAS and ROM, 10MWT, 6MD, TUG, and BBS after 4 weeks improved from the baseline. Furthermore, the ankle MAS and ROM improved significantly within 2 weeks, as did the 10MWT and 6MD over the total 4 weeks. In conclusion, it is suggested that a better improvement of ambulation and balance, as well as spasticity, would be found with intensive rehabilitation following BTXA treatment for lower limb spasticity.

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: 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: The effectiveness of clozapine is clearly superior to other antipsychotics in the treatment of refractory schizophrenia. Clozapine leads to various side effects, and therefore many patients are forced to discontinue. In this study, we analyzed the registry database of all cases in Japan to identify risk factors for discontinuation of clozapine. Methods: The Clozaril patient monitoring service® (CPMS) database from July 31, 2009 to January 26, 2020 was acquired. We defined the following exclusion criteria: patients who had ever taken clozapine by a non-CPMS method, such as an individual import or clinical trial, patients who did not receive clozapine after being enrolled in CPMS, and patients with initial doses other than 12.5 mg (outside the current protocol). Therefore, all patients in this study are new users. Multivariate Cox regression analysis was used to investigate independent risk factors associated with time to discontinuation of clozapine. Results: We identified 8,263 patients as the study population. Clozapine discontinuation was significantly associated with age 40 and older [hazard ratio (HR)=1.66, p<0.001], intolerance to olanzapine (HR=1.31, p=0.018), previous treatment with clozapine (HR=1.30, p=0.001), and leukocyte counts <6,000/mm3 (HR=1.24, p<0.001). The Kaplan-Meier curves for clozapine discontinuation by age group revealed that older age at the time of clozapine introduction tended to have lower continuation rates. Conclusion Careful administration is important because patients with these factors have a high risk of discontinuation. In addition, the initiation of clozapine during the younger period was more effective and more tolerated.