A history of multiple concussions does not alter the transcranial doppler-based assessment of the neurovascular coupling response
Bibliographic record
Abstract
Objective To determine how a history of 3+ concussions alters elevations in cerebral blood velocity (CBV) in the posterior cerebral artery (PCA) during visual tasks. Design Retrospective Cohort. Setting Laboratory. Participants 136 male contact-sport athletes (19.1±1.4 years, 66 football, 70 hockey) were recruited; 39 presented with 0 previous concussions, 16 with 3+ previous concussions; exclusion criteria included history of concussion within 6 months. Intervention Transcranial Doppler ultrasound indexed PCA-CBV during a series of visual tasks. Participants closed their eyes (20-seconds) and, when prompted, opened their eyes to complete a visual task (40-seconds). Testing occurred prior to the start of their athletic season. The visual trial raw traces were averaged together to enhance the signal-to-noise ratio of outcome measurements. The independent variable tested was concussion history. Outcomes Eyes-closed CBV (cm/s), peak elevation in CBV after eyes-open (cm/s), relative change in CBV (%), and total activation during the first 30 seconds of the task (indexed via area under the curve-AUC) Main results Independent samples T-Tests indicated there were no effects of concussion history on any outcome: Eyes-closed CBV (p=0.950), peak CBV (p=0.903), % CBV elevation (p=0.593), and AUC (p=0.718). Conclusions A history of multiple concussions does not alter the cerebrovasculature’s ability to maintain nutrient delivery required for visual challenges in cortical areas supplied by the PCA. This is an important finding; despite the long-term neurocognitive deficits associated with a history of concussions, the transcranial Doppler assessment of neurovascular coupling appears intact for this population of younger adult contact-sport athletes. 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 | 0.003 |
| 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) | 0.003 | 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".