Symptom correlates of cerebral blood flow following acute concussion
Bibliographic record
Abstract
Concussion is associated with significant symptoms within hours to days post-injury, including disturbances in physical function, cognition, sleep and emotion. However, little is known about how subjective impairments correlate with objective measures of cerebrovascular function following brain injury. This study examined the relationship between symptoms and cerebral blood flow (CBF) in individuals following sport-related concussion. Seventy university level athletes had CBF measured using Arterial Spin Labelling (ASL), including 35 with acute concussion and 35 matched controls and their symptoms were assessed using the Sport Concussion Assessment Tool 3 (SCAT3). For concussed athletes, greater total symptom severity was associated with elevated posterior cortical CBF, although mean CBF was not significantly different from matched controls (p = 0.46). Examining symptom clusters, athletes reporting greater cognitive symptoms also had lower frontal and subcortical CBF, relative to athletes with greater somatic symptoms. The “cognitive” and “somatic” subgroups also exhibited significant differences in CBF relative to controls (p ≤ 0.026). This study demonstrates objective CBF correlates of symptoms in recently concussed athletes and shows that specific symptom clusters may have distinct patterns of altered CBF, significantly extending our understanding of the neurobiology of concussion and traumatic brain injury.
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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) | 0.001 | 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".