Contributions of neuroimaging, balance testing, electrophysiology and blood markers to the assessment of sport-related concussion
Bibliographic record
Abstract
OBJECTIVE: To review the diagnostic tests and investigations used in the management of sports concussion, in the adult and paediatric populations, to (a) monitor the severity of symptoms and deficits, (b) track recovery and (c) advance knowledge relating to the natural history and neurobiology of the injury. DESIGN: Qualitative literature review of the neuroimaging, balance testing, electrophysiology, blood marker and concussion literature. INTERVENTION: PubMed and Medline databases were reviewed for investigations used in the management of adult and paediatric concussion, including structural imaging (computerised tomography, magnetic resonance imaging, diffusion tensor imaging), functional imaging (single photon emission computerised tomography, positron emission tomography, functional magnetic resonance imaging), spectroscopy (magnetic resonance spectroscopy, near infrared spectroscopy), balance testing (Balance Error Scoring System, Sensory Organization Test, gait testing, virtual reality), electrophysiological tests (electroencephalography, evoked potentials, event related potentials, magnetoencephalography, heart rate variability), genetics (apolipoprotein E4, channelopathies) and blood markers (S100, neuron-specific enolase, cleaved Tau protein, glutamate). RESULTS: For the adult and paediatric populations, each test has been classified as being: (1) clinically useful, (2) a research tool only or (3) not useful in sports-related concussion. CONCLUSIONS: The current status of the diagnostic tests and investigations is analysed, and potential directions for future research are provided. Currently, all tests and investigations, with the exception of clinical balance testing, remain experimental. There is accumulating research, however, that shows promise for the future clinical application of functional magnetic resonance imaging in sport concussion assessment and management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".