Neurovascular coupling response is maintained despite exposure to repetitive sub-concussive head trauma over the course of one contact-sport season
Bibliographic record
Abstract
Objective To examine how head-impact exposures affect the elevation in cerebral blood velocity (CBV) in the posterior cerebral artery (PCA) during visual tasks. Design Prospective Cohort. Setting Laboratory. Participants To date: 40 male contact-sport athletes (19.4±1.2 years) and 3 cross-country athletes (20.0±1.0 years) have completed testing (non-contact controls). Intervention Transcranial Doppler ultrasound indexed PCA CBV during visual tasks. Participants closed their eyes (20-seconds), and when prompted, opened them and completed a visual task (40-seconds). Testing occurred prior-to and upon-completion-of the competitive athletic season. Raw traces from each trial were averaged to enhance the signal-to-noise ratio of outcome measurements. Independent variable tested was time (2). Outcome Eyes-closed CBV (cm/s), peak elevation in CBV (cm/s), relative change in CBV (%) and total activation during the first 30 seconds of the task (indexed via area under the curve-AUC). Head-impact exposure was characterised in a subset of contact-sport athletes (n=29) using the xPatch (X2 Biosystems). Main results RM-ANOVA indicated the contact-sport season had no effects on any outcome metrics: Eyes-closed CBV (p=0.181), peak CBV (p=0.117),% CBV elevation (p=0.252) and AUC (p=0.366), despite experiencing cumulative peak linear accelerations of 8147.2±6215.5 g, and cumulative peak rotational accelerations of 34.5×106 ± 59.0×106 rad/?s2. Conclusions The results from this study suggest neurovascular coupling metrics are maintained throughout a contact-sport season. This indicates nutrient delivery is maintained for neurocognitive challenges despite possible impairments in cerebrovasculature’s ability to buffer blood pressure challenges associated elevations in rotational accelerations experienced during a contact-sport season. 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 | 0.001 |
| 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) | 0.002 | 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".