Effects of high-frequency transcranial magnetic stimulation on functional performance in individuals with incomplete spinal cord injury: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) has been investigated as a new tool in neurological rehabilitation of individuals with spinal cord injury (SCI). However, due to the inconsistent results regarding the effects of rTMS in people with SCI, a randomized controlled double-blind crossover trial is needed to clarify the clinical utility and to assess the effect size of rTMS intervention in this population. Therefore, this paper describes a study protocol designed to investigate whether the use of rTMS can improve the motor and sensory function, as well as reduce spasticity in patients with incomplete SCI. METHODS: A double-blind randomized sham-controlled crossover trial will be performed by enrolling 20 individuals with incomplete SCI. Patients who are at least six months post incomplete SCI (aged 18-60 years) will be recruited through referral by medical practitioners or therapists. Individuals will be randomly assigned to either group 1 or group 2 in a 1:1 ratio, with ten individuals in each group. The rTMS protocol will include ten sessions of high-frequency rTMS (5 Hz) over the bilateral lower-limb motor area positioned at the vertex (Cz). Clinical evaluations will be performed at baseline and after rTMS active and sham. DISCUSSION: rTMS has produced positive results in treating individuals with physical impairments; thus, it might be promising in the SCI population. The results of this study may provide new insights to motor rehabilitation thereby contributing towards the better usage of rTMS in the SCI population. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02899637 . Registered on 25 August 2016.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
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 | 0.033 | 0.029 |
| Meta-epidemiology (narrow) | 0.009 | 0.003 |
| Meta-epidemiology (broad) | 0.018 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.049 | 0.009 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".