Baseline Predictors of Response to Repetitive Task Practice in Chronic Stroke

Author:

Dimyan Michael A.123ORCID,Harcum Stacey1,Ermer Elsa12,Boos Amy F.24,Conroy Susan S.1ORCID,Liu Fang5,Horn Linda B.6,Xu Huichun7,Zhan Min8,Chen Hegang8,Whitall Jill6,Wittenberg George F.12346ORCID

Affiliation:

1. VA Maryland Health Care System, Baltimore VA Medical Center, Baltimore, MD, USA

2. Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA

3. Geriatrics Research, Education and Clinical Center and Maryland Exercise and Robotics Center of Excellence, Veterans Affairs Medical Center, Older Americans Independence Center, University of Maryland School of Medicine, Baltimore, MD, USA

4. Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA

5. Rehab & Neural Engineering Labs, Department of Physical Medicine & Rehabilitation, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA

6. Department of Physical Therapy and Rehabilitation Science, University of Maryland School of Medicine, Baltimore, MD, USA

7. Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA

8. Department of Epidemiology and Preventative Medicine, University of Maryland School of Medicine, Baltimore, MD, USA

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.

Funder

VA Maryland Health Care System

Publisher

SAGE Publications

Subject

General Medicine

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