White Matter Hyperintensity in Athletes: A cross‐sectional study
Bibliographic record
Abstract
BACKGROUND: . This study investigates the relationships between concussion history, vascular risk factors, and WMH volume, as well as their associations with cognitive outcomes in athletes with RHI. METHOD: This cross-sectional study included 96 male professional contact sports athletes enrolled in the Canadian Concussion Centre's concussion monitoring program and 21 male controls without a history of concussion. WMH volumes were quantified from T2-weighted FLAIR magnetic resonance imaging using automated segmentation. Vascular risk factors were assessed via questionnaires. Cognitive function was evaluated with standardized neuropsychological tests, and composite scores for memory and executive function were derived using normative data for both athletes and controls. All analyses controlled for age. Linear regression models evaluated associations between concussion history (treated as a continuous variable), WMH volume, cognitive performance, and vascular risk factors. RESULT: Athletes had significantly greater WMH volume than controls (median 1.3 ml vs. 0.8 ml, p = 0.024), although the difference was insignificant when normalized to total intracranial volume. Age was the strongest predictor of WMH volume (β = 0.3851, p < 0.001) and was associated with reduced hippocampal (right: β = -0.012, p < 0.001; left: β = -0.011, p = 0.001) and amygdala volumes (right: β = -0.003, p = 0.003; left: β = -0.004, p = 0.003). Concussion history was associated with declines in executive function (β = -0.0244, p = 0.034) and memory (β = -0.0539, p = 0.027) but not with WMH volume. Vascular risk factors were not significantly associated with WMH or cognitive outcomes. CONCLUSION: Athletes with RHI demonstrated higher WMH volume than controls, mainly driven by age rather than concussion history or vascular risk factors. Concussion history was associated with cognitive impairments in executive function and memory, emphasizing the importance of cognitive monitoring in aging athletes and the need for longitudinal studies to explore the interplay between RHI, aging, cognition, and neurodegeneration.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".