Deans' stroke musings: Can Neurological Biomarkers of Brain Impairment Be Used to Predict Poststroke Motor Recovery? A Systematic Review

Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Thursday, August 11, 2016

Can Neurological Biomarkers of Brain Impairment Be Used to Predict Poststroke Motor Recovery? A Systematic Review

Does no one else think this is fucking stupid to try to predict recovery without even acknowledging that even knowing this doesn't do survivors one damn bit of good because no protocols exist to map recovery to damaged areas? Everyone in stroke is completely flying blind.
http://nnr.sagepub.com/content/early/2016/08/05/1545968316662708.abstract

Bokkyu Kim, MS1
Carolee Winstein, PhD1 ⇑

¹University of Southern California, Los Angeles, CA, USA

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.