Auwal Abdullahi, Bishir Sabo, Umaru Muhammad Badaru, Wim Saeys, Steven Truijen
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The result showed that, the whole model significantly explained the total variance by 88.4%, <i>F</i>(14, 144) = 32.870, <i>R</i> <sup>2</sup> = 0. 0.781, <i>p</i> < 0.001. However, in the final model, only four independent variables in the order of degree of predictability, amount of use of the limb in the real world (Beta = 0.455, <i>p</i> = 0.003), intensity of practice during rehabilitation session (Beta = 0.321, <i>p</i> < 0.001), wrist spasticity (Beta = 0.148, <i>p</i> = 0.004) and side affected (Beta = 0.093, <i>p</i> = 0.033) significantly predicted recovery of motor function.</p><p><strong>Conclusion: </strong>Encouraging the use of the limb in the real world may be more important than practice during rehabilitation session in the clinic or in the laboratory.</p>","PeriodicalId":23227,"journal":{"name":"Translational Neuroscience","volume":"13 1","pages":"453-459"},"PeriodicalIF":1.8000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9743202/pdf/","citationCount":"1","resultStr":"{\"title\":\"Factors influencing recovery of upper limb motor function during constraint-induced movement therapy for people with stroke.\",\"authors\":\"Auwal Abdullahi, Bishir Sabo, Umaru Muhammad Badaru, Wim Saeys, Steven Truijen\",\"doi\":\"10.1515/tnsci-2022-0260\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>The aim of this study is to determine the personal and clinical factors that can predict recovery of motor function in people with stroke.</p><p><strong>Methods: </strong>Characteristics of the study participants such as age, sex, time since stroke and type of stroke, motor function, shoulder pain, amount and quality of use of the affected limb in the real world, wrist and elbow spasticity, handedness, central post-stroke pain and dose of massed practice were recorded. The data obtained were analyzed using descriptive statistics and multiple regression.</p><p><strong>Results: </strong>A total of 144 patients with stroke with mean age, 58.71 ± 19.90 years participated in the study. The result showed that, the whole model significantly explained the total variance by 88.4%, <i>F</i>(14, 144) = 32.870, <i>R</i> <sup>2</sup> = 0. 0.781, <i>p</i> < 0.001. However, in the final model, only four independent variables in the order of degree of predictability, amount of use of the limb in the real world (Beta = 0.455, <i>p</i> = 0.003), intensity of practice during rehabilitation session (Beta = 0.321, <i>p</i> < 0.001), wrist spasticity (Beta = 0.148, <i>p</i> = 0.004) and side affected (Beta = 0.093, <i>p</i> = 0.033) significantly predicted recovery of motor function.</p><p><strong>Conclusion: </strong>Encouraging the use of the limb in the real world may be more important than practice during rehabilitation session in the clinic or in the laboratory.</p>\",\"PeriodicalId\":23227,\"journal\":{\"name\":\"Translational Neuroscience\",\"volume\":\"13 1\",\"pages\":\"453-459\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9743202/pdf/\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Translational Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1515/tnsci-2022-0260\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1515/tnsci-2022-0260","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 1
摘要
目的:本研究的目的是确定预测脑卒中患者运动功能恢复的个人和临床因素。方法:记录研究对象的年龄、性别、中风时间和中风类型、运动功能、肩部疼痛、实际使用患肢的数量和质量、手腕和肘部痉挛、惯用手、中风后中枢性疼痛和大量练习的剂量等特征。所得资料采用描述性统计和多元回归分析。结果:共144例脑卒中患者参与研究,平均年龄58.71±19.90岁。结果表明,整个模型显著解释了总方差的88.4%,F(14,144) = 32.870, r2 = 0。0.781, p < 0.001。然而,在最终的模型中,只有四个自变量按照可预测性的顺序,分别是肢体在现实世界中的使用量(Beta = 0.455, p = 0.003)、康复期间的练习强度(Beta = 0.321, p < 0.001)、手腕张力(Beta = 0.148, p = 0.004)和侧患(Beta = 0.093, p = 0.033)显著预测运动功能的恢复。结论:鼓励在现实世界中使用肢体可能比在诊所或实验室的康复过程中练习更重要。
Factors influencing recovery of upper limb motor function during constraint-induced movement therapy for people with stroke.
Objective: The aim of this study is to determine the personal and clinical factors that can predict recovery of motor function in people with stroke.
Methods: Characteristics of the study participants such as age, sex, time since stroke and type of stroke, motor function, shoulder pain, amount and quality of use of the affected limb in the real world, wrist and elbow spasticity, handedness, central post-stroke pain and dose of massed practice were recorded. The data obtained were analyzed using descriptive statistics and multiple regression.
Results: A total of 144 patients with stroke with mean age, 58.71 ± 19.90 years participated in the study. The result showed that, the whole model significantly explained the total variance by 88.4%, F(14, 144) = 32.870, R2 = 0. 0.781, p < 0.001. However, in the final model, only four independent variables in the order of degree of predictability, amount of use of the limb in the real world (Beta = 0.455, p = 0.003), intensity of practice during rehabilitation session (Beta = 0.321, p < 0.001), wrist spasticity (Beta = 0.148, p = 0.004) and side affected (Beta = 0.093, p = 0.033) significantly predicted recovery of motor function.
Conclusion: Encouraging the use of the limb in the real world may be more important than practice during rehabilitation session in the clinic or in the laboratory.
期刊介绍:
Translational Neuroscience provides a closer interaction between basic and clinical neuroscientists to expand understanding of brain structure, function and disease, and translate this knowledge into clinical applications and novel therapies of nervous system disorders.