Next-Day Serum Glial Fibrillary Acidic Protein Levels to Aid Diagnosis of Sport-Related Concussion
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Previous studies on sport-related concussion (SRC) may have measured brain injury blood-based biomarker, glial fibrillary acidic protein (GFAP), either before or after its peak, potentially underestimating the diagnostic value. The primary aim of this study was to evaluate the diagnostic performance of serum GFAP at 24 hours post-SRC. Secondary objectives included assessing whether the timing of sample collection relative to an Australian football match (with or without SRC) affected GFAP levels, evaluating if combining GFAP with symptoms improved discrimination of SRC compared with symptoms alone, and determining the diagnostic utility of serum neurofilament light (NfL) levels at 24 hours post-SRC. METHODS: In a prospective cohort study, adult male and female Australian football players of the Victorian Amateur Football Association (Melbourne, Australia) with and without SRC had blood sampled around 24 hours postinjury/postmatch. GFAP and NfL levels were quantified using Simoa assays, and area under the curve (AUC) values were calculated for time bins of 16-24 hours, 24-32 hours, and 36-52 hours. Symptom severity at blood collection was assessed using the Sport Concussion Assessment Tool 5 (SCAT). RESULTS: = 0.01). Serum NfL had a limited diagnostic value (AUC ≤0.60). DISCUSSION: Serum GFAP measured at 16-24 hours following potential or suspected SRC may be a useful objective aid to SRC diagnosis.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".