The effects of prior concussion and contact sport participation on the brain
Bibliographic record
Abstract
Objective there is currently limited information on the neurobiological effects of contact sport participation, and interactions with history of concussion. The goal of this study is to examine the interactions between history of concussion and contact sport participation, using biomarkers of cerebral metabolites, brain function, and white matter microstructure. Design cross-sectional study. Setting sport medicine clinic, affiliated with inter-university sport program (secondary care). Participants 43 athletes without concussion in the past 6 months were recruited, including 22 athletes without prior concussion (13 non-contact, 9 contact; 11 female) and 21 athletes with a history of concussion (13 non-contact, 8 contact; 11 female). Outcome measures Magnetic Resonance Imaging (MRI) was used to measure brain biomarkers: MRI spectroscopy to evaluate cerebral metabolites; functional MRI to assess brain function; diffusion tensor imaging for white matter microstructure. Main results athletes in contact sports with prior concussion showed significant differences in brain structure and function, relative to athletes in non-contact sports, and those in contact sports without prior injury. This included significantly elevated glutamate ratios, decreased functional connectivity of the visual and motor systems, and increased fractional anisotropy of white matter. Conclusions This study provides the first multi-modal MRI data showing altered brain structure and function in athletes with a history of concussion and interactions with contact sport participation. These findings provide strong preliminary evidence that athletes in contact sports may be more vulnerable to the long-term effects of sport concussion. Competing interests None.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".