A Prospective, Multicenter Study to Assess the Safety and Efficacy of Translingual Neurostimulation Plus Physical Therapy for the Treatment of a Chronic Balance Deficit Due to Mild-to-Moderate Traumatic Brain Injury
Bibliographic record
Abstract
OBJECTIVES: Translingual neurostimulation (TLNS) studies indicate improved outcomes in neurodegenerative disease or spinal cord injury patients. This study was designed to assess the safety and efficacy of TLNS plus targeted physical therapy (PT) in people with a chronic balance deficit after mild-to-moderate traumatic brain injury (mmTBI). MATERIALS AND METHODS: This international, multicenter, randomized study enrolled 122 participants with a chronic balance deficit who had undergone PT following an mmTBI and had plateaued in recovery. Randomized participants received PT plus either high-frequency pulse (HFP; n = 59) or low-frequency pulse (LFP; n = 63) TLNS. The primary efficacy and safety endpoints were the proportion of sensory organization test (SOT) responders (SOT composite score improvement of ≥15 points) and fall frequency after five weeks of treatment, respectively. RESULTS: The proportion of SOT responders was significant in the HFP + PT (71.2%) and LFP + PT (63.5%) groups compared with baseline (p < 0.0005). For the pooled population, the SOT responder rate was 67.2% (p < 0.00005), and there were clinically and statistically significant improvements in SOT composite scores after two and five weeks (p < 0.0005). Both groups had reductions in falls and headache disability index scores. Mean dynamic gait index scores in both groups also significantly increased from baseline at weeks 2 and 5. CONCLUSIONS: Significant improvements in balance and gait, in addition to headaches, sleep quality, and fall frequency, were observed with TLNS plus targeted PT; in participants who had a chronic balance deficit following an mmTBI and had plateaued on prior conventional physiotherapy.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".