What is the lowest threshold to make a diagnosis of concussion?
Bibliographic record
Abstract
OBJECTIVE: The purpose of this review is to examine the evidence for determining the lowest threshold for diagnosing a sport-related concussion. DATA SOURCES: MEDLINE, CINAHL, EMBASE, Mosby's Index, PsycEXTRA, PsycINFO and Scopus. Key words included sports concussion, concussion assessment, diagnosis, concussion symptoms, onfield assessment and sports-related traumatic brain injury. RESULTS: The majority of concussions in sport occur without loss of consciousness or frank neurological signs. Some of the hallmark signs of acute concussion include mental confusion, memory and balance disturbance. Over the course of the first 24 h, the most common symptoms include headache, nausea, dizziness and balance problems, blurred vision or other visual disturbance, confusion, memory loss and 'fatigue'. Symptoms such as tiredness, irritability, nervousness or anxiety, sleep disturbance and sensitivity to light or noise may be noticed in the days after injury. The pathophysiology of sports concussion remains poorly understood. There appears to be a period of vulnerability following concussion in which an overlapping injury might cause magnified pathophysiology. CONCLUSIONS: Sport-related concussions can be difficult to diagnose. Concussion produces an evolving constellation of somatic, cognitive and neurobehavioral symptoms that are typically most severe during the earliest acute postinjury period (ie, within the first 24-48 h) and diminish over a matter of several days to weeks in the majority of athletes. Athletes suspected of concussion should be removed from play and evaluated thoroughly.
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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 | 0.022 | 0.169 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.012 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".