The Optometric Management of Concussion
Bibliographic record
Abstract
Traumatic brain injury is a major public health problem that affects millions of people annually and hundreds of people experience brain injury daily. Many of these individuals develop visual symptoms. Optometrists play a prominent role in the management of patients with concussion-associated vision deficits and persistent concussion symptoms. At present, there is no accepted optometric standard of care for individuals with concussion. Patients receiving optometric concussion related care would benefit from a standardized evidence-based concussion management process. \nThe purpose of this project was to determine the current assessment methods and prescribing practices of optometrists seeing individuals with persistent concussion-associated vision deficits in private practice and at a university academic optometry clinic. \n \nStudy 1: \nA retrospective review examined the frequency of visual assessments and management strategies at an academic university optometry clinic. A total of 238 patient files were examined. Of the 238 patient files, 119 individuals had persistent concussion symptoms (concussed group) and 119 individuals did not have concussion (non-concussed cohort). The frequency of visual assessments (ocular structure and visual function) and management strategies were determined. A chi square test was used to compare the frequency of assessments and management strategies between cohorts. In the concussed group, an emphasis on visual function and management strategies, for example assessments of vergence, saccades, pursuits and stereopsis were observed in comparison to the reference group. In non-concussed individuals, ocular structure assessments (e.g., posterior segment, anterior segment and confrontation visual field) were more prevalent than in the concussed cohort. It is important to note that ocular structure assessments did not include assessments conducted by the referring optometrists. Diagnostic drugs, for example tropicamide and anesthetics, were used more commonly in the non-concussed group, while cycloplegia was more prevalent in the concussed group. \n \nStudy 2: \nA 6-question online survey was distributed to optometric provincial and national regulators and associations in Canada. Questions pertaining to visual assessments, prescribed medications and supplements, advice about daily living activity, appointment duration and appointment follow-up were asked. Analysis consisted of binning and determining the frequency of responses. Of the 199 responses received, 142 were completed and analysis was only conducted from these responses. A total of 128 optometrists managed concussion and 13 optometrists did not. The top reasons for optometrists who did not manage concussion was referral and no training. Ocular structure assessments were more prevalent than visual function and management strategies of concussion. Optometrists most frequently recommended Omega 3 (54%) and oral supplements (38%). The majority of optometrist’s (64%) advice on daily living activity was to limit physical and cognitive activity, the second most common suggestion was to rest (12%). The majority of optometrists, 57%, employed 30 to 60-minute assessments and over one-fifth conducted follow-up appointments within 2-months. \nConclusion: \nThis project informs optometrists on the state of concussion management in Canadian private practice and at a university academic optometry clinic. \nFindings can be used to aid in the development of standardized strategies for the optometric management of concussion and related regulatory decisions. This can lead to reductions in persistent post-concussive symptoms, improved patient outcomes, and overall improved quality of life.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".