P.023 Impact of repeated nonconcussive hits on neurophysiological parameters in collegiate football athletes
Bibliographic record
Abstract
Background: A nonconcussive injury occurs from an impact to the head that does not result in overt symptoms. However, growing evidence suggests that the accumulation of nonconcussive impacts can result in neurological symptoms, either due to injury to the blood vessel or as a result of altered neural functioning. Despite this, the effects of repeated nonconcussive impacts on cerebral blood flow (CBF) and cerebrovascular reactivity (CVR) remain unclear. Methods: Twenty Canadian male collegiate football athletes were imaged at three time points: pre-, mid-, and post-season (3T Siemens Prisma) with arterial spin labelling (CBF) and a blood oxygen level-dependent sequence during which hypercapnia was induced (CVR; RA-MR, Thornhill Medical, Toronto, CA). Results: Significant changes in CBF and CVR were observed at both mid- and post-season compared to pre-season baseline measurements. Conclusions: Alterations in CBF and CVR may precede the emergence of neurocognitive symptoms later in life that may be associated with repetitive nonconcussive impacts. These findings highlight the potential of CBF and CVR as early biomarkers for trauma-related brain changes in contact sports. Future studies should investigate the long-term consequences of these physiological alterations and implement player safety protocols designed to reduce the prevalence of nonconcussive impacts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.006 | 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".