Evaluating Cerebrovascular Reactivity during the Early Symptomatic Phase of Sport Concussion
Bibliographic record
Abstract
Cerebrovascular reactivity (CVR) indexes the ability of blood vessels to respond to vasoactive stimuli and may be a sensitive biomarker of concussion. However, alterations in whole-brain CVR remain poorly understood during the early symptomatic phase of injury. In this study, CVR was assessed using blood-oxygenation-level dependent functional magnetic resonance imaging (BOLD fMRI) combined with a respiratory challenge paradigm; resting cerebral blood flow (CBF) was also evaluated using arterial spin labeling (ASL). Imaging data were collected for 77 university-level athletes, including 56 athletic uninjured controls and 21 concussed athletes scanned in the early symptomatic phase of injury (≤7 days post-injury). The normal response to respiratory challenge was assessed in the athletic control group, in which a robust whole-brain response was observed. The concussed athletes were then compared to a matched subset of controls. Concussion was associated with greater reductions in BOLD activity during the early phase of the respiratory task, localized primarily in frontal and pre-frontal areas, whereas no significant effects on resting global CBF were observed. In addition, greater symptom severity was associated with greater reductions in BOLD response, with effects distributed throughout the brain. This study establishes fMRI with respiratory challenge as a robust method for assessing acute concussion-related alterations in CVR. Moreover, it highlights the importance of examining neurovascular response to physiological stressors after a concussion.
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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 | 0.001 | 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) | 0.000 | 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 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".