Altered Vestibular Balance Function in Combat Sport Athletes
Bibliographic record
Abstract
Combat sports pose a risk for accumulative injuries to the nervous system, yet fighters have remained an understudied population. Here, our purpose was to determine whether repetitive blows to the head have an effect on vestibular balance reflexes in combat sports athletes. We compared lower-limb muscle responses evoked with electrical vestibular stimuluation (EVS) between fighters (boxing/muay thai) and non-fighter controls. Each participant received stochastic vestibular stimulation (0-25 Hz, ±3 mA) over their mastoid processes while they stood relaxed with their head to the left or right. Surface electromyography was recorded from the medial gastrocnemius and soleus muscles bilaterally. Short and medium latency response (SLR/MLR) peaks were significantly delayed in the fighter group compared to controls. SLR and MLR peak amplitudes were also significantly lower in fighters. Fighter-estimated cumulative repetitive head impact (RHI) events demonstrated strong positive correlations with the timing of SLR and MLR peaks. Cumulative RHI events also negatively correlated with peak MLR amplitude and response gain at frequencies above 5 Hz. Our results provide evidence of a progressive vestibular impairment in combat sports athletes, potentially resulting from blows to the head accumulated in sparring practice and competitive bouts throughout their careers. Taken together, EVS-based vestibular assessments may provide a valuable clinical diagnostic tool and help better inform "return-to-play" and career-length decisions for not only combat sports athletes, but potentially other populations at risk of RHIs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".