Self-perceived Impact of Glaucomatous Visual Field Loss and Visual Disabilities on Driving Difficulty and Cessation
Bibliographic record
Abstract
PURPOSE: To investigate if glaucoma severity and the presence of self-reported glare and difficulty with dark adaptation are associated with driving difficulty or cessation. PATIENTS AND METHODS: Individuals with glaucoma, age 50+ and visual acuity in the better eye ≥20/50 were included. Glaucoma severity was defined by the visual field mean deviation (MD) in the better eye and was classified into 2 groups: mild (MD>-6 dB) and moderate/severe (MD≤-6 dB). Patient responses to the glare and dark adaptation subscales in Glaucoma Quality of Life-15 questionnaire were used to measure relevant visual disability. Associations were assessed utilizing prevalence ratios (PR). RESULTS: A total of 99 participants (57% female) were included with 19% (19/99) reporting driving cessation. Patients with moderate/severe glaucoma when compared with mild glaucoma reported a significantly higher percentage of driving cessation (33% vs. 8%; P=0.002), presence of glare (27% vs. 6%; P=0.012), and difficulty with dark adaptation (31% vs. 10%; P=0.011).Individuals with self-perceived difficulty with dark adaptation were about 4 times more likely than those without to have difficulty driving at night (adjusted PR=3.94; P<0.0001) or in poor driving conditions (adjusted PR=4.09; P=0.0002). Self-reported glare was associated with an increased risk of driving difficulty in poor driving conditions (PR=4.17; P=0.05). CONCLUSIONS: Patients with moderate/severe glaucomatous visual field loss reported significantly higher percentage of driving cessation, presence of glare and difficulty with dark adaptation. Difficulty with dark adaptation was significantly associated with difficulty driving at night or in poor driving conditions. Further studies are needed to confirm these findings.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".