Non‐invasive Brain Stimulation Can Reduce Unilateral Spatial Neglect after Stroke: <scp>ELETRON</scp> Trial
Bibliographic record
Abstract
OBJECTIVE: Rehabilitation top-down techniques based on brain stimulation present variable outcomes in unilateral spatial neglect (USN) after stroke. This study aimed to examine the effects of physical therapy after anodal and cathodal transcranial direct current stimulation (A-tDCS and C-tDCS, respectively) to improve visuospatial and functional impairments in individuals with USN after stroke. METHODS: This double-blinded, pilot randomized clinical trial enrolled patients with USN after ischemic stroke. Randomization was stratified according to the Behavior Inattention Test-Conventional (BIT-C) and Catherine Bergego Scale (CBS). Outpatient physical therapy was conducted for 7.5 weeks after 20 minutes of tDCS. The primary outcome was the USN degree evaluated by the BIT-C. Secondary outcomes were the difference in CBS score, stroke severity (National Institutes of Health Stroke Scale [NIHSS]), disability (modified Rankin Scale), autonomy (Barthel Index, Functional Independence Measure), and quality of life (EuroQol Group 5-Dimension Self-Report Questionnaire). Outcomes were analyzed using an analysis of covariance model corrected by age, baseline NIHSS, and baseline BIT-C. Pairwise post hoc comparisons were performed using Bonferroni correction. RESULTS: In the primary outcomes, A-tDCS led to greater improvement in BIT-C after intervention (mean difference [MD] = 18.4, 95% confidence interval [CI] = 3.9-32.8, p = 0.008) compared to sham. However, no significant differences were observed between A-tDCS and C-tDCS (MD = 13.9, 95% CI = -0.3 to 28.1, p = 0.057), or C-tDCS and sham (MD = 4.5, 95% CI = -9.7 to 18.8, p = 0.99). There were no significant differences between groups in terms of secondary outcomes. INTERPRETATION: A-tDCS associated with physical therapy can decrease the severity of USN after stroke. However, these preliminary findings must be confirmed by collecting additional evidence in a larger phase 3 trial. ANN NEUROL 2022;92:400-410.
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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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".