Saccadic Eye Movements in Mild Traumatic Brain Injury: A Pilot Study OPEN ACCESS
Bibliographic record
Abstract
OBJECTIVE: To investigate whether repeat saccadic reaction time (SRT) measurements using a portable saccadometer is useful to monitor patients with mild traumatic brain injury (mTBI). METHODS: Seven patients with newly-diagnosed mTBI and five agematched controls were prospectively recruited from an emergency Department. Saccadic eye movements, symptom self-reporting and neuropsychological tests were performed within one week of injury and again at follow-up three weeks post-injury. Control patients underwent saccade recordings at similar intervals. RESULTS: Median saccade reaction times were significantly prolonged within one week post-injury in mTBI compared to controls. At follow-up assessment there was no significant between-groups difference. Changes in median SRT between the two assessments were not statistically significant. Four of the seven mTBI patients showed significantly increased SRT at follow-up; three of the mTBI patients and all controls showed no significant change. Among the three mTBI patients with persistent decreased SRT, two experienced loss of consciousness and reported the greatest symptoms, while the third was the only subject with significant decrease in neuropsychological testing scores at both assessments. CONCLUSION: In three of seven mTBI patients, saccadic eye movements remained delayed within three weeks post-injury. These three patients also showed persistent symptoms or no improvement on neuropsychological testing. This pilot study using a portable saccadometer suggests that comparing SRT from three weeks post-injury to that within one week of injury may be useful for early detection of a subpopulation at risk of persistent disability from mTBI. This finding suggests that further investigation in a large study population is warranted. Les saccades oculaires dans le traumatisme cérébral léger : une étude pilote.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".