http://nnr.sagepub.com/content/31/1/3?etoc
- Bokkyu Kim, MS1
- Carolee Winstein, PhD1⇑
- Carolee Winstein, Motor Behavior and Neurorehabilitation Laboratory, Division of Biokinesiology and Physical Therapy, University of Southern California, 1540 Alcazar Street, CHP 155, Los Angeles, CA 90089, USA. Email: winstein@usc.edu
Abstract
Background. There is growing
interest to establish recovery biomarkers, especially neurological
biomarkers, in order to develop new
therapies and prediction models for the promotion
of stroke rehabilitation and recovery. However, there is no consensus
among
the neurorehabilitation community about which
biomarker(s) have the highest predictive value for motor recovery. Objective. To review the evidence and determine which neurological biomarker(s) meet the high evidence quality criteria for use in
predicting motor recovery.
Methods. We
searched databases for prognostic neuroimaging/neurophysiological
studies. Methodological quality of each study was assessed
using a previously employed comprehensive 15-item
rating system. Furthermore, we used the GRADE approach and ranked the
overall
evidence quality for each category of neurologic
biomarker.
Results. Seventy-one articles met our inclusion
criteria; 5 categories of neurologic biomarkers were identified:
diffusion tensor
imaging (DTI), transcranial magnetic stimulation
(TMS), functional magnetic resonance imaging (fMRI), conventional
structural
MRI (sMRI), and a combination of these biomarkers.
Most studies were conducted with individuals after ischemic stroke in
the
acute and/or subacute stage (~70%). Less than
one-third of the studies (21/71) were assessed with satisfactory
methodological
quality (80% or more of total quality score).
Conventional structural MRI and the combination biomarker categories
ranked
“high” in overall evidence quality.
Conclusions. There were 3 prevalent methodological limitations: (a) lack of cross-validation, (b) lack of minimal clinically important difference (MCID) for motor outcomes, and (c)
small sample size. More high-quality studies are needed to establish
which neurological biomarkers are the best predictors
of motor recovery after stroke. Finally, the
quarter-century old methodological quality tool used here should be
updated by
inclusion of more contemporary methods and
statistical approaches.
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