Deans' stroke musings: Multimodal Imaging Biomarker-Based Model Using Stratification Strategies for Predicting Upper Extremity Motor Recovery in Severe Stroke Patients

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.

Monday, March 7, 2022

Multimodal Imaging Biomarker-Based Model Using Stratification Strategies for Predicting Upper Extremity Motor Recovery in Severe Stroke Patients

Survivors don't want predictions of failure to recover. They want protocols that deliver recovery. DO YOU NOT KNOW HOW TO DO YOUR FUCKING JOB? OR WHAT THAT JOB IS?

Multimodal Imaging Biomarker-Based Model Using Stratification Strategies for Predicting Upper Extremity Motor Recovery in Severe Stroke Patients

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Jungsoo Lee, PhD

, Heegoo Kim, BS, Jinuk Kim, MS, ...

First Published December 31, 2021 Research Article Find in PubMed

Abstract

Background.

Various prognostic biomarkers for upper extremity (UE) motor recovery after stroke have been reported. However, most have relatively low predictive accuracy in severe stroke patients.

Objective.

This study suggests an imaging biomarker-based model for effectively predicting UE recovery in severe stroke patients.

Methods.

Of 104 ischemic stroke patients screened, 42 with severe motor impairment were included. All patients underwent structural, diffusion, and functional magnetic resonance imaging at 2 weeks and underwent motor function assessments at 2 weeks and 3 months after stroke onset. According to motor function recovery at 3 months, patients were divided into good and poor subgroups. The value of multimodal imaging biomarkers of lesion load, lesion volume, white matter integrity, and cortical functional connectivity for motor recovery prediction was investigated in each subgroup.

Results.

Imaging biomarkers varied depending on recovery pattern. The integrity of the cerebellar tract (P = .005, R² = .432) was the primary biomarker in the good recovery group. In contrast, the sensory-related corpus callosum tract (P = .026, R² = .332) and sensory-related functional connectivity (P = .001, R² = .531) were primary biomarkers in the poor recovery group. A prediction model was proposed by applying each biomarker in the subgroup to patients with different motor evoked potential responses (P < .001, R² = .853, root mean square error = 5.28).

Conclusions.

Our results suggest an optimized imaging biomarker model for predicting UE motor recovery after stroke. This model can contribute to individualized management of severe stroke in a clinical setting.

Keywords

stroke, recovery, multimodal imaging, prediction