Impaired cerebral blood flow regulation and cognition in male football players
Bibliographic record
Abstract
Football players are at increased risk of neurodegeneration, the likely consequence of repetitive mechanical trauma caused by heading the ball. However, to what extent a history of heading the ball affects cerebral blood flow (CBF) regulation and its potential relationship to cognitive impairment is unknown. To address this, we recruited 16 concussion‐free male amateur football players (age: 25 ± 6 y) with a history of heading the ball (18 ± 6 y) and 18 sex, age, education, and activity‐matched controls with no prior history of contact sport participation or concussion. Cerebral perfusion was measured at rest and in response to both hyper/hypocapnia to determine cerebrovascular reactivity to carbon dioxide (CVRCO2HYPER/HYPO) using transcranial Doppler ultrasound and capnography, with the sum reflecting the cerebral vasomotor range. Cognition and visuomotor coordination were assessed using the Montreal cognitive assessment (MoCA) and the Grooved Pegboard Dexterity Test (GPD), respectively. While no differences in cerebral perfusion were observed (p = 0.938), CVRCO2HYPER/HYPO (p = 0.038/p = 0.025), cerebral vasomotor range (p = 0.002), MoCA (p = 0.027), and GPD performance (dominant hand, P ≤ 0.001) were consistently lower in the players compared to controls. These findings are the first to demonstrate that CBF regulation and cognition are collectively impaired in male football players with history of heading the ball, which may contribute to 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".