Neuropsychological Correlates of Diplopia (Double Vision) in Motorists with Traumatic Brain Injury
Bibliographic record
Abstract
Background:The symptom of double vision, known in ophthalmology as diplopia, is observed with various neurological conditions such as in multiple sclerosis, Parkinson's disease, and the post-concussion syndrome. Our study examines the correlates of diplopia in survivors of high impact motor vehicle accidents (MVAs).Method: Data on diplopia were available for 65 patients injured in MVAs (mean age of 38.1 years, SD=13.1;24 men, 41 women).All patients were assessed using the Rivermead Post-Concussion Symptoms Questionnaire, Immediate Concussion Symptoms scale, the Post-MVA Neurological Symptoms (PMNS) scale, Insomnia Severity Index, as well as selected items from the Brief Pain Inventory (ratings of worst, least, and of average pain) and from the Whiplash Disability Questionnaire (ratings of depression, anger, and anxiety).Results: Diplopia was reported by 27.7% of the patients.Ratings of diplopia correlated at a significant level (p<.05, 2-tailed) with the total Rivermead post-concussive score (r=.46) after the item "double vision" was removed from the Rivermead's total score, and also with the total score on the PMNS scale (r=.35).Diplopia also correlated significantly with Rivermead's post-concussive symptoms of blurred vision, oversensitivity to bright lights (photosensitivity), restlessness, dizziness, nausea, and problems with slow speed of thinking (the rs ranged from .30 to .57).With respect to individual items of the PMNS scale, diplopia correlated significantly to impaired balance, hand tremor, reduced control over hand or arm, and to some loss of bladder control (the rs ranged from .30 to .41).Discussion and Conclusions: Diplopia was reported by 27.7% of survivors of high impact MVAs and was correlated with various other post-concussive symptoms, especially blurred vision, photosensitivity, and impaired balance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".