Monitoring the acute and subacute recovery of cognitive ocular motor changes after a sports-related concussion
Bibliographic record
Abstract
Identifying when recovery from a sports-related concussion (SRC) has occurred remains a challenge in clinical practice. This study investigated the utility of ocular motor (OM) assessment to monitor recovery post-SRC between sexes and compared to common clinical measures. From 139 preseason baseline assessments (i.e. before they sustained an SRC), 18 (12 males, 6 females) consequent SRCs were sustained and the longitudinal follow-ups were collected at 2, 6, and 13 days post-SRC. Participants completed visually guided, antisaccade (AS), and memory-guided saccade tasks requiring a saccade toward, away from, and to a remembered target, respectively. Changes in latency (processing speed), visual-spatial accuracy, and errors were measured. Clinical measures included The Sports Concussion Assessment Tool, King-Devick test, Stroop task, and Digit span. AS latency was significantly longer at 2 days and returned to baseline by 13-days post-SRC in females only (P < 0.001). Symptom numbers recovered from 2 to 6 days and 13 days (P < 0.05). Persistently poorer AS visual-spatial accuracy was identified at 2, 6 and 13 days post-SRC (P < 0.05) in both males and females but with differing trajectories. Clinical measures demonstrated consistent improvement reminiscent of practice effects. OM saccade assessment may have improved utility in tracking recovery compared to conventional measures and between sexes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".