A.03 Cerebral perfusion and its relationship to post-concussion syndrome in mild traumatic brain injury: a prospective controlled cohort study
Bibliographic record
Abstract
Background: Persistent post-concussive symptoms (PCS) have been linked to increased cortical network activation and decreased cerebrovascular reactivity. Decreased cerebral perfusion could help explain PCS and may be a biomarker to track recovery. Methods: Children (ages 8 to 18 years) symptomatic with PCS at one month post-injury were studied. Children who recovered following a mTBI (asymptomatic group) and healthy children acted as controls. Pseudocontinuous arterial spin labeling MRI was used to quantify cerebral blood flow (CBF). All subjects were imaged at approximately 40 days post-injury. Symptomatic group underwent repeat neuroimaging 4-5 weeks later. Results: Seventy-two participants (14.1 years; 95% CIs: 13.5, 14.8) underwent neuroimaging at 40 days post-injury. Global CBF was significantly higher in the symptomatic group compared to healthy controls, and lower in the asymptomatic group (F(2,57) 9.734 p<0.001). Symptomatic children had increased CBF in the frontal and occipital regions, and asymptomatic children had decreased CBF in the temporal regions compared to healthy controls. CBF decreased in symptomatic children over time. CBF was a predictor of cognition (R2=0.235;p=0.001). Conclusions: Cerebral perfusion is altered in children with mTBI and is associated with recovery trajectory. Asymptomatic children had decreased CBF suggesting cerebral recovery is ongoing. Further longitudinal studies are required to determine if these perfusion patterns continue to change over time.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".