Brain stimulation and constraint for hemiparesis after perinatal stroke: The PLASTIC CHAMPS trial
Bibliographic record
Abstract
Background: Perinatal stroke causes hemiparetic cerebral palsy. Constraint therapy (CIMT) improves function in congenital hemiparesis and adult stroke. Repetitive transcranial magnetic stimulation (rTMS) may improve function in adult stroke. The two have not been tested in perinatal stroke. Methods: PLASTIC CHAMPS ( www.clinicaltrials.gov/NCT01189058 ) was a controlled factorial trial of rTMS and CIMT in perinatal-stroke hemiparesis. Children 6-18 years participated in a 2 week peer-supported motor learning camp, randomized to daily inhibitory rTMS (1200 stimulations, contralesional M1), CIMT, both or neither. Primary outcomes were Assisting Hand Assessment (AHA) and Canadian Occupational Performance Measure (COPM) at 1, 8, and 24 weeks. Quality-of-life, safety and tolerability were evaluated. Change was assessed across treatment groups over time (linear mixed effects model). Results: All forty-five subjects completed the trial (median 11.4yrs). COPM scores increased >100% with maximal gains at 6 months (p<0.002). Addition of rTMS and/or CIMT doubled the chances of clinically significant gains. Combined rTMS+CIMT resulted in larger AHA gains at all time points (6 months p=0.006). CIMT or rTMS alone had more modest effects. Neither treatment decreased function in either hand. Procedures were well tolerated. Conclusions: Children with hemiparesis participating in intensive, psychosocial rehabilitation programs perceive marked increases in function. Non-invasive brain stimulation may enhance motor learning therapy in perinatal stroke hemiparesis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".