MEDITOXIN® Treatment in Subjects With Post-Stroke Upper Limb Spasticity

Author(s):  
Toxicon ◽  
2016 ◽  
Vol 123 ◽  
pp. S35 ◽  
Author(s):  
Jean-Michel Gracies ◽  
Allison Brashear ◽  
Christina Marciniak ◽  
Robert Jech ◽  
Marta Banach ◽  
...  

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Hernan F Bayona ◽  
Pratik Y Chhatbar ◽  
Gottfried Schlaug ◽  
Wayne Feng

Introduction: Upper-limb spasticity is a very disabling complication after stroke. There has been no simple clinical standard scale to predict spasticity immediately after stroke. This study aims to develop a simple bedside grading scale with the information collected during the acute phase to predict spasticity at 3 month post-stroke Methods: This is a prospective cohort study (Prediction and Imaging Biomarker of Post-stroke Motor Recovery) of patients with first-ever acute ischemic stroke with various degrees of motor impairment. NIH stroke scale (NIHSS) was assessed 2-7 days after onset of stroke symptoms. Modified Ashworth Spasticity Scale was used as an assessment tool in biceps, wrist flexors and finger flexors at 90 days (± 15 days) and score ≥2 at any muscle was considered as severe spasticity. Infarction volume was measured based on the lesion on MRI/DWI. Independent predictors of upper-limb spasticity at 90 days were identified by multivariate logistic regression. A risk stratification scale was developed with weighting independent predictors based on beta coefficient. Results: One hundred twenty three patients were recruited for this study. Covariates associated with upper-limb spasticity are NIHSS arm score (p<0.0001), sub-cortical location (p=0.004) and lesion volume >65 cc (p=0.025). The proposed grading scale is summation of individual points as followed: NIHSS Arm Score: =4 (2 point), <4 (0 point); infarct location: sub-cortical (1 point), non sub-cortical (0 point); infarct volume: ≥65 cc (1 point), <65cc (0 point). The rates of severe upper limb spasticity for the bedside spasticity scale, in order 0-4, are 8.9%, 29.2%, 65%, 88.7%, 96.2%. In other words, the likelihood of developing severe spasticity increases steadily using the score. Conclusion: A simple bedside grading scale can effectively predict severe post-stroke upper-limb spasticity at 90 days. Validation with an independent external dataset is a planned next step.


Open Medicine ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. 227-231 ◽  
Author(s):  
Yi Jin ◽  
Yuan Zhao

AbstractObjectiveThe purpose of this study was to evaluate the incidence rate of post-stroke upper limb spasticity and its correlation with cerebral infarction site.MethodsA total of 498 inpatient and outpatient cases are included in the present study. The post-stroke upper limb spasticity rate of different cerebral infarction site was calculated.ResultsA total of 498 patients with cerebral infarction are enrolled in this study. Of these patients, 91 have dropped out and 407 have completed the study. Of the completed cases, 172 are in the spasm group and 235 are in the non-spasm group. The total incidence of upper limb spasticity is 34.5%. The incidences of upper extremity spasms are 12.5%, 20%, 22.5%, 35%, 40%, and 42.5% in 2 weeks, 1 month, 2 months, 3 months, 6 months, and 12 months, respectively. The incidence of upper extremity spasms increases with time. The incidences of upper limb spasticity are 12.1%, 63.3%, 58.5%, 9.4% and 8.3% when cerebral infarction occurs in the cortical and subcortical mixed areas, basal ganglia and internal capsule, cerebralcortex, brainstem and cerebellum respectively. The incidence of upper limb spasticity varies in different infarction sites (P < 0.05).ConclusionThe post-stroke upper limb spasticity rates were different according to the different cerebral infarction site. Patients with the ganglia and internal capsule infarctions had the highest risk of developing post-stroke upper limb spasticity.


Toxins ◽  
2013 ◽  
Vol 5 (5) ◽  
pp. 983-991
Author(s):  
Woo-Jin Kim ◽  
Witsanu Kumthornthip ◽  
Byung Oh ◽  
Eun Yang ◽  
Nam-Jong Paik

2017 ◽  
Vol 15 (1) ◽  
pp. 27-30 ◽  
Author(s):  
Hong-yan Di ◽  
Shu-kai Han ◽  
Xiao-lin Du ◽  
Wen-wen Li ◽  
Jing Jia

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