Advances in Sport Concussion Assessment: From Behavioral to Brain Imaging Measures
Bibliographic record
Abstract
Given that the incidence of sports-related concussion is considered to have reached epidemic proportions, in the past 15 years we have witnessed an explosion of research in this field. The purpose of the current review is to compare the results provided by the different assessment tools used in the scientific literature in order to gain a better understanding of the sequelae and recovery following a concussion. Until recently, the bulk of the has literature focused on the immediate outcome in the hours and days post-injury as a means to plan the safest return-to-play strategy. This has led to the development of several assessment batteries that are relatively easy and rapid to administer and that allow for multiple testing sessions. The main conclusion derived from that literature is that cognitive symptoms tend to resolve within 1 week. However, accumulating evidence indicates that cognitive testing should be viewed as one of several complementary tools necessary for a comprehensive assessment of concussion. Including an objective measure of postural stability increases the sensitivity of the return-to-play decision-making process and minimizes the consequences of mitigating factors (e.g., practice effects and motivation) on neuropsychological test results. This is consistent with findings that symptom severity, neuropsychological function, and postural stability do not appear to be related or affected to the same degree after a concussion. Furthermore, recent evidence from brain imaging, including event-related potentials and functional and metabolic imaging, suggest abnormalities in the electrical responses, metabolic balance, and oxygen consumption of neurons that persist several months after the incident. We explain this apparent discrepancy in recovery by suggesting an initial and rapid phase of functional recovery driven by compensatory mechanisms and brain plasticity, which is followed by a prolonged neuronal recovery period during which subtle deficits in brain functioning are present but not apparent to standard clinical assessment tools.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".