An investigation of neuroinjury biomarkers after sport-related concussion: from the subacute phase to clinical recovery
Bibliographic record
Abstract
OBJECTIVES: To characterise a panel of neuroinjury-related blood biomarkers after sport-related concussion (SRC). We hypothesised significant differences in biomarker profiles between athletes with SRC and healthy controls at both subacute and medical clearance time points. METHODS: Thirty-eight interuniversity athletes were recruited over two athletic seasons (n = 19 SRC; n = 19 healthy matched-control). High-sensitivity immunoassay was used to evaluate 11 blood analytes at both the subacute phase after SRC and at medical clearance. RESULTS: Univariate analysis identified elevated circulating peroxiredoxin-6 (PRDX-6) in athletes with SRC compared to healthy controls at the subacute time point. Multivariate analyses yielded similar results in the subacute phase, but identified both PRDX-6 and T-tau as significant contributors to class separation between athletes with SRC and controls at medical clearance. CONCLUSIONS: Our results are consistent with the increasing recognition that physiological recovery after SRC extends beyond clinical recovery. Blood biomarkers appear to be useful in elucidating the biology of brain restitution after SRC. However, their implementation requires mindfulness of factors such as academic stress, exercise, and injury heterogeneity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".