A Prospective Transcranial Doppler Ultrasound-Based Evaluation of the Acute and Cumulative Effects of Sport-Related Concussion on Neurovascular Coupling Response Dynamics
Bibliographic record
Abstract
Sport-related concussion has been shown to alter cerebral blood flow (CBF) both acutely and chronically, and may exert cumulative effects across multiple injuries. Such dysfunction may be mediated by trauma-induced deficits to CBF control mechanisms, though our understanding of these effects is limited, including dynamics of neurovascular coupling (NVC) responses (i.e., CBF responses to neurologic demand). A total of 179 junior-level contact sport athletes completed preseason testing; 42 reported never having experienced a concussion (Hx−) while 31 had endured three or more (Hx3+). A total of 18 athletes suffered concussions during the study period and were re-tested 3 days, 2 weeks, and 1 month post-injury. NVC dynamics were indexed via CBF velocity in the posterior (PCAv) and middle (MCAv) cerebral arteries during cycles of 20 sec eyes closed and 40 sec eyes open to a visual stimulus (reading). Acutely following concussion, peak rate of PCAv increase during the activation phase was delayed by over 50% and PCAv response magnitude was elevated by over 30%, compared with preseason. Response magnitude remained elevated at 2 weeks despite symptom resolution. Independent medical clearance for full return-to-play was inversely related to the magnitude of increase in the NVC response at 3 days post-injury. No post-injury changes were observed in MCAv, blood pressure, or end-tidal carbon dioxide levels during visual stimulation. No NVC metric differences were observed between the Hx− and Hx3+ groups at preseason. Via multiple potential mechanisms, acute sport-related concussion may induce compensatory alterations in NVC response dynamics that may be related to clinical recovery. Such effects do not appear to be persistent across multiple injuries.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".