Document Type

Article

Publication Date

1-2015

Abstract

Objective

This study was undertaken to better understand the high variability in response seen when treating human subjects with restorative therapies poststroke. Preclinical studies suggest that neural function, neural injury, and clinical status each influence treatment gains; therefore, the current study hypothesized that a multivariate approach incorporating these 3 measures would have the greatest predictive value.

Methods

Patients 3 to 6 months poststroke underwent a battery of assessments before receiving 3 weeks of standardized upper extremity robotic therapy. Candidate predictors included measures of brain injury (including to gray and white matter), neural function (cortical function and cortical connectivity), and clinical status (demographics/medical history, cognitive/mood, and impairment).

Results

Among all 29 patients, predictors of treatment gains identified measures of brain injury (smaller corticospinal tract [CST] injury), cortical function (greater ipsilesional motor cortex [M1] activation), and cortical connectivity (greater interhemispheric M1–M1 connectivity). Multivariate modeling found that best prediction was achieved using both CST injury and M1–M1 connectivity (r2 = 0.44, p  = 0.002), a result confirmed using Lasso regression. A threshold was defined whereby no subject with >63% CST injury achieved clinically significant gains. Results differed according to stroke subtype; gains in patients with lacunar stroke were best predicted by a measure of intrahemispheric connectivity.

Interpretation

Response to a restorative therapy after stroke is best predicted by a model that includes measures of both neural injury and function. Neuroimaging measures were the best predictors and may have an ascendant role in clinical decision making for poststroke rehabilitation, which remains largely reliant on behavioral assessments. Results differed across stroke subtypes, suggesting the utility of lesion-specific strategies.

Comments

This is the accepted version of the following article:

Burke Quinlan, E., Dodakian, L., See, J., McKenzie, A., Le, V., Wojnowicz, M., Shahbaba, B. and Cramer, S. C. (2015), Neural function, injury, and stroke subtype predict treatment gains after stroke. Ann Neurol., 77: 132–145. doi: 10.1002/ana.24309

which has been published in final form at DOI: 10.1002/ana.24309. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

Peer Reviewed

1

Copyright

American Neurological Association

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.