Visual Rehabilitation as a Treatment Tool for Collegiate Athletes Post-mTBI to Improve Return to Sport Outcomes
Bibliographic record
Abstract
Introduction: Fifty percent of the 46 000 concussions seen in Canada are sports related, with post-concussive syndrome (PCS) impacting up to 30% of those patients. Individuals who experience PCS will often report headaches, dizziness, and blurred vision with visual disturbances reported in 20-85% depending on the nature of the visual deficit. A concussion is a type of traumatic brain injury (TBI) and results from an external insult leading to axonal shearing of nerve fibers, which are responsible for the signs and symptoms experienced. Current best practice in treatment involves initial rest followed by increasing aerobic activity as well as visual rehabilitation to reduce the symptoms associated with a TBI. Visual rehabilitation following TBI can take many forms with the vast majority of research focusing on convergence insufficiency (CI). CI is a condition in which the individual’s eyes are unable to work together when looking at nearby objects and is a common binocular vision deficit after TBI. Near point convergence (NPC) occurs when the visual axes intersect at the maximal effort leading to blurred vision, dizziness, difficulty concentrating and reading. Clinicians should consider screening for NPC and using as a rehabilitation tool when managing TBI.\nPurpose: The purpose of this literature review was to determine whether visual rehabilitation for CI and NPC is an effective treatment strategy to reduce symptoms associated with a TBI and improve athletes return to life and sport.\nRecommendations: Research demonstrates that visual rehabilitation for CI and NPC deficiencies will decrease patient reported symptoms and will return NPC to normal ranges.\nConclusion: Diagnosis, assessment, and rehabilitation of a TBI should involve the visual system due to the integral connections in all aspects of the brain leading to signs and symptoms which can impair an individual’s function of daily living. Further research regarding different visual markers in TBI is needed regarding treatment, specifically surrounding parameters
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".