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Record W2885770191 · doi:10.2196/10848

Connectivity as a Predictor of Responsiveness to Transcranial Direct Current Stimulation in People with Stroke: Protocol for a Double-Blind Randomized Controlled Trial

2018· article· en· W2885770191 on OpenAlexvenueno aff
Ellana Welsby, Michael C. Ridding, Susan Hillier, Brenton Hordacre

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research CouncilSylvia and Charles Viertel Charitable Foundation
KeywordsTranscranial direct-current stimulationPhysical medicine and rehabilitationRandomized controlled trialTranscranial magnetic stimulationBrain stimulationStroke (engine)Motor cortexMedicineRehabilitationNeurorehabilitationStimulationNeuroplasticityPsychologyPhysical therapyNeuroscienceInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Stroke can have devastating consequences for an individual's quality of life. Interventions capable of enhancing response to therapy would be highly valuable to the field of neurological rehabilitation. One approach is to use noninvasive brain stimulation techniques, such as transcranial direct current stimulation, to induce a neuroplastic response. When delivered in combination with rehabilitation exercises, there is some evidence that transcranial direct current stimulation is beneficial. However, responses to stimulation are highly variable. Therefore biomarkers predictive of response to stimulation would be valuable to help select appropriate people for this potentially beneficial treatment. OBJECTIVE: The objective of this study is to investigate connectivity of the stimulation target, the ipsilesional motor cortex, as a biomarker predictive of response to anodal transcranial direct current stimulation in people with stroke. METHODS: This study is a double blind, randomized controlled trial (RCT), with two parallel groups. A total of 68 participants with first ever ischemic stroke with motor impairment will undertake a two week (14 session) treatment for upper limb function (Graded Repetitive Arm Supplementary Program; GRASP). Participants will be randomized 2:1 to active:sham treatment groups. Those in the active treatment group will receive anodal transcranial direct current stimulation to the ipsilesional motor cortex at the start of each GRASP session. Those allocated to the sham treatment group will receive sham transcranial direct current stimulation. Behavioural assessments of upper limb function will be performed at baseline, post treatment, 1 month follow-up and 3 months follow-up. Neurophysiological assessments will include magnetic resonance imaging (MRI), electroencephalography (EEG) and transcranial magnetic stimulation (TMS) and will be performed at baseline, post treatment, 1 month follow-up (EEG and TMS only) and 3 months follow-up (EEG and TMS only). RESULTS: Participants will be recruited between March 2018 and December 2018, with experimental testing concluding in March 2019. CONCLUSIONS: Identifying a biomarker predictive of response to transcranial direct current stimulation would greatly assist clinical utility of this novel treatment approach. TRIAL REGISTRATION: Australia New Zealand Clinical Trials Registry ACTRN12618000443291; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12618000443291 (Archived by WebCite at http://www.webcitation.org/737QOXXxt). REGISTERED REPORT IDENTIFIER: RR1-10.2196/10848.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.058
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.036
Meta-epidemiology (narrow)0.0090.004
Meta-epidemiology (broad)0.0220.008
Bibliometrics0.0030.004
Science and technology studies0.0040.005
Scholarly communication0.0050.004
Open science0.0040.003
Research integrity0.0100.010
Insufficient payload (model declined to judge)0.0580.012

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.253
GPT teacher head0.543
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2018
Admission routes1
Has abstractyes

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