Evidence map›Paper›PMID 33324923›Full record

ReviewNeurological research and practice2020

Recovery from stroke: current concepts and future perspectives.

Christian Grefkes, Gereon R Fink

Registry-linked trialAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Neurological research and practice, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06574737 (Use of Surface Electromyography as a Tools to Predict Upper Extremity Recovery Function After Stroke), which is not on this map. Cited by 276 papers, 17 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
276citing papers in PubMed, 17 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06574737 recruitingnot on this mapstarted 2024, after this paper: background citation

Use of Surface Electromyography as a Tools to Predict Upper Extremity Recovery Function After Stroke

Typeobservational_patient_registrySponsorUniversitas PadjadjaranRan2024 to 2025Enrolled30ConditionsUpper Extremity Paresis, Muscle Contracture Upper Arm, Stroke
3 · Its place in the literature

Who cites it

276 citing papers in PubMed, 17 syntheses or guidelines pooled it.

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  14. A systematic review and in silico analysis of studies investigating the ischemic penumbra proteome in animal models of experimental stroke.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2024
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216 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Christian GrefkesCognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Jülich, 52425 Jülich, Germany.ORCID 0000-0002-1656-720X
Gereon R FinkCognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Jülich, 52425 Jülich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stroke is a leading cause of acquired, permanent disability worldwide. Although the treatment of acute stroke has been improved considerably, the majority of patients to date are left disabled with a considerable impact on functional independence and quality of life. As the absolute number of stroke survivors is likely to further increase due to the demographic changes in our aging societies, new strategies are needed in order to improve neurorehabilitation. The most critical driver of functional recovery post-stroke is neural reorganization. For developing novel, neurobiologically informed strategies to promote recovery of function, an improved understanding of the mechanisms enabling plasticity and recovery is mandatory. This review provides a comprehensive survey of recent developments in the field of stroke recovery using neuroimaging and non-invasive brain stimulation. We discuss current concepts of how the brain reorganizes its functional architecture to overcome stroke-induced deficits, and also present evidence for maladaptive effects interfering with recovery. We demonstrate that the combination of neuroimaging and neurostimulation techniques allows a better understanding of how brain plasticity can be modulated to promote the reorganization of neural networks. Finally, neurotechnology-based treatment strategies allowing patient-tailored interventions to achieve enhanced treatment responses are discussed. The review also highlights important limitations of current models, and finally closes with possible solutions and future directions.

Indexed as

Brain stimulationMotorNeuroimagingNeurorehabilitationTMS

Identifiers

PMID33324923
PMCPMC7650109

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.