M. Dimyan, Stacey Harcum, Elsa Ermer, A. Boos, Susan S. Conroy, Fang Liu, L. B. Horn, Huichun Xu, M. Zhan, Hegang Chen, J. Whitall, G. Wittenberg
{"title":"慢性脑卒中患者重复性任务练习反应的基线预测因素","authors":"M. Dimyan, Stacey Harcum, Elsa Ermer, A. Boos, Susan S. Conroy, Fang Liu, L. B. Horn, Huichun Xu, M. Zhan, Hegang Chen, J. Whitall, G. Wittenberg","doi":"10.1177/15459683221095171","DOIUrl":null,"url":null,"abstract":"Background Repetitive task practice reduces mean upper extremity motor impairment in populations of patients with chronic stroke, but individual response is highly variable. A method to predict meaningful reduction in impairment in response to training based on biomarkers and other data collected prior to an intervention is needed to establish realistic rehabilitation goals and to effectively allocate resources. Objectives To identify prognostic factors and better understand the biological substrate for reductions in arm impairment in response to repetitive task practice among patients with chronic (≥6 months) post-stroke hemiparesis. Methods The intervention is a form of repetitive task practice using a combination of robot-assisted therapy and functional arm use in real-world tasks. Baseline measures include the Fugl-Meyer Assessment, Wolf Motor Function Test, Action Research Arm Test, Stroke Impact Scale, questionnaires on pain and expectancy, MRI, transcranial magnetic stimulation, kinematics, accelerometry, and genomic testing. Results Mean increase in FM-UE was 4.6 ± 1.0 SE, median 2.5. Approximately one-third of participants had a clinically meaningful response to the intervention, defined as an increase in FM ≥ 5. The selected logistic regression model had a receiver operating curve with AUC = .988 (Std Error = .011, 95% Wald confidence limits: .967–1) showed little evidence of overfitting. Six variables that predicted response represented impairment, functional, and genomic measures. Conclusion A simple weighted sum of 6 baseline factors can accurately predict clinically meaningful impairment reduction after outpatient intensive practice intervention in chronic stroke. Reduction of impairment may be a critical first step to functional improvement. Further validation and generalization of this model will increase its utility in clinical decision-making.","PeriodicalId":56104,"journal":{"name":"Neurorehabilitation and Neural Repair","volume":"36 1","pages":"426 - 436"},"PeriodicalIF":3.7000,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Baseline Predictors of Response to Repetitive Task Practice in Chronic Stroke\",\"authors\":\"M. Dimyan, Stacey Harcum, Elsa Ermer, A. Boos, Susan S. Conroy, Fang Liu, L. B. Horn, Huichun Xu, M. Zhan, Hegang Chen, J. Whitall, G. Wittenberg\",\"doi\":\"10.1177/15459683221095171\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background Repetitive task practice reduces mean upper extremity motor impairment in populations of patients with chronic stroke, but individual response is highly variable. A method to predict meaningful reduction in impairment in response to training based on biomarkers and other data collected prior to an intervention is needed to establish realistic rehabilitation goals and to effectively allocate resources. Objectives To identify prognostic factors and better understand the biological substrate for reductions in arm impairment in response to repetitive task practice among patients with chronic (≥6 months) post-stroke hemiparesis. Methods The intervention is a form of repetitive task practice using a combination of robot-assisted therapy and functional arm use in real-world tasks. Baseline measures include the Fugl-Meyer Assessment, Wolf Motor Function Test, Action Research Arm Test, Stroke Impact Scale, questionnaires on pain and expectancy, MRI, transcranial magnetic stimulation, kinematics, accelerometry, and genomic testing. Results Mean increase in FM-UE was 4.6 ± 1.0 SE, median 2.5. Approximately one-third of participants had a clinically meaningful response to the intervention, defined as an increase in FM ≥ 5. The selected logistic regression model had a receiver operating curve with AUC = .988 (Std Error = .011, 95% Wald confidence limits: .967–1) showed little evidence of overfitting. Six variables that predicted response represented impairment, functional, and genomic measures. Conclusion A simple weighted sum of 6 baseline factors can accurately predict clinically meaningful impairment reduction after outpatient intensive practice intervention in chronic stroke. Reduction of impairment may be a critical first step to functional improvement. Further validation and generalization of this model will increase its utility in clinical decision-making.\",\"PeriodicalId\":56104,\"journal\":{\"name\":\"Neurorehabilitation and Neural Repair\",\"volume\":\"36 1\",\"pages\":\"426 - 436\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2022-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neurorehabilitation and Neural Repair\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/15459683221095171\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neurorehabilitation and Neural Repair","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/15459683221095171","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Baseline Predictors of Response to Repetitive Task Practice in Chronic Stroke
Background Repetitive task practice reduces mean upper extremity motor impairment in populations of patients with chronic stroke, but individual response is highly variable. A method to predict meaningful reduction in impairment in response to training based on biomarkers and other data collected prior to an intervention is needed to establish realistic rehabilitation goals and to effectively allocate resources. Objectives To identify prognostic factors and better understand the biological substrate for reductions in arm impairment in response to repetitive task practice among patients with chronic (≥6 months) post-stroke hemiparesis. Methods The intervention is a form of repetitive task practice using a combination of robot-assisted therapy and functional arm use in real-world tasks. Baseline measures include the Fugl-Meyer Assessment, Wolf Motor Function Test, Action Research Arm Test, Stroke Impact Scale, questionnaires on pain and expectancy, MRI, transcranial magnetic stimulation, kinematics, accelerometry, and genomic testing. Results Mean increase in FM-UE was 4.6 ± 1.0 SE, median 2.5. Approximately one-third of participants had a clinically meaningful response to the intervention, defined as an increase in FM ≥ 5. The selected logistic regression model had a receiver operating curve with AUC = .988 (Std Error = .011, 95% Wald confidence limits: .967–1) showed little evidence of overfitting. Six variables that predicted response represented impairment, functional, and genomic measures. Conclusion A simple weighted sum of 6 baseline factors can accurately predict clinically meaningful impairment reduction after outpatient intensive practice intervention in chronic stroke. Reduction of impairment may be a critical first step to functional improvement. Further validation and generalization of this model will increase its utility in clinical decision-making.
期刊介绍:
Neurorehabilitation & Neural Repair (NNR) offers innovative and reliable reports relevant to functional recovery from neural injury and long term neurologic care. The journal''s unique focus is evidence-based basic and clinical practice and research. NNR deals with the management and fundamental mechanisms of functional recovery from conditions such as stroke, multiple sclerosis, Alzheimer''s disease, brain and spinal cord injuries, and peripheral nerve injuries.