A Prospective Transcranial Doppler Ultrasound-Based Evaluation of the Effects of Repetitive Subconcussive Head Trauma on Neurovascular Coupling Dynamics
Bibliographic record
Abstract
OBJECTIVE: To determine the effects of repetitive subconcussive head trauma on neurovascular coupling (NVC) responses. DESIGN: Prospective cohort study collected between September 2013 and December 2016. SETTING: University laboratory. PARTICIPANTS: One hundred seventy-nine elite, junior-level (age, 19.6 ± 1.5 years) contact sport (ice hockey, American football) athletes recruited for preseason testing. Fifty-two nonconcussed athletes returned for postseason testing. Fifteen noncontact sport athletes (age, 20.4 ± 2.2 years) also completed preseason and postseason testing. EXPOSURE(S): Subconcussive sport-related head trauma. MAIN OUTCOME MEASURES: Dynamics of NVC were estimated during cycles of 20 seconds eyes closed and 40 seconds eyes open to a visual stimulus (reading) by measuring cerebral blood flow (CBF) velocity in the posterior (PCA) and middle (MCA) cerebral arteries via transcranial Doppler ultrasound. RESULTS: Both athlete groups demonstrated no significant differences in PCA or MCA NVC dynamics between preseason and postseason, despite exposure to a median of 353.5 (range, 295.0-587.3) head impacts (>2g) over the course of the season for contact sport athletes. CONCLUSIONS: Within the context of growing concern over detrimental effects of repetitive subconcussive trauma, the current results encouragingly suggest that the dynamics of NVC responses are not affected by 1 season of participation in junior-level ice hockey or American football. This is an important finding because it indicates an appropriate postseason CBF response to elevated metabolic demand with increases in neural activity.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".