Synergistic effect of combined transcranial direct current stimulation/constraint-induced movement therapy in children and young adults with hemiparesis: study protocol
Bibliographic record
Abstract
BACKGROUND: Perinatal stroke occurs in more than 1 in 2,500 live births and resultant congenital hemiparesis necessitates investigation into interventions which may improve long-term function and decreased burden of care beyond current therapies ( http://www.cdc.gov/ncbddd/cp/data.html ). Constraint-Induced Movement Therapy (CIMT) is recognized as an effective hemiparesis rehabilitation intervention. Transcranial direct current stimulation as an adjunct treatment to CIMT may potentiate neuroplastic responses and improve motor function. The methodology of a clinical trial in children designed as a placebo-controlled, serial -session, non-invasive brain stimulation trial incorporating CIMT is described here. The primary hypotheses are 1) that no serious adverse events will occur in children receiving non-invasive brain stimulation and 2) that children in the stimulation intervention group will show significant improvements in hand motor function compared to children in the placebo stimulation control group. METHODS/DESIGN: A randomized, controlled, double-blinded clinical trial. Twenty children and/or young adults (ages 8-21) with congenital hemiparesis, will be enrolled. The intervention group will receive ten 2-hour sessions of transcranial direct current stimulation combined with constraint-induced movement therapy and the control group will receive sham stimulation with CIMT. The primary outcome measure is safety assessment of transcranial direct current stimulation by physician evaluation, vital sign monitoring and symptom reports. Additionally, hand function will be evaluated using the Assisting Hand Assessment, grip strength and assessment of goals using the Canadian Occupational Performance Measure. Neuroimaging will confirm diagnoses, corticospinal tract integrity and cortical activation. Motor cortical excitability will also be examined using transcranial magnetic stimulation techniques. DISCUSSION: Combining non-invasive brain stimulation and CIMT interventions has the potential to improve motor function in children with congenital hemiparesis beyond each intervention independently. Such a combined intervention has the potential to benefit an individual throughout their lifetime. TRIAL REGISTRATION: Clinicaltrials.gov, NCT02250092 Registered 18 September 2014.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".