Whiplash and Concussion: Similar Acute Changes in Middle-Latency SEPs
Bibliographic record
Abstract
OBJECTIVE: Middle-latency somatosensory evoked potentials (SEPs) following median nerve stimulation can provide a sensitive measure of cortical function. We sought to determine whether the mechanical forces of whiplash injury or concussion alter normal processing of middle-latency SEPs. METHODS: In a cross-sectional pilot study 20 subjects with whiplash were investigated (50% between 0.5-2 months and 50% between 6-41 months post injury) and compared to 83 healthy subjects using a standard middle-latency SEP procedure. In a subsequent prospective study subjects with either acute whiplash (n=13) or Grade 3 concussion (n=16) were investigated within 48 hours and again three months post injury. RESULTS: In the pilot study the middle-latency SEP component N60 was significantly increased in the ten subjects investigated within two months after whiplash. In contrast, the ten subjects examined more than six months after injury showed normal latencies. In the prospective study N60 latencies were increased after whiplash and concussion when tested within 48 hours of injury. At three months, latencies were improved though still significantly different from controls post whiplash and concussion. CONCLUSIONS: Both whiplash injury and concussion alter processing of the middle-latency SEP component N60 in the acute post traumatic period. The acute changes appear to normalize between three-six months post injury. The SEP similarities suggest that the overlapping clinical symptomatology post whiplash and concussion may reflect a similar underlying mechanism of rotational mild traumatic brain injury.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".