Visual hallucinations in patients undergoing intravitreal anti-VEGF agents in northern British Columbia: Prevalence and characteristics.
Bibliographic record
Abstract
Objective: Visual hallucinations (Charles Bonnet Syndrome) is a common phenomenon seen in patients with poor vision. The aim of this study was to determine the prevalence and characteristics of visual hallucinations in patients receiving intravitreal anti-VEGF (vascular endothelial growth factor) treatment in a northern community. Study Design: Cross-sectional survey. Methods: Participants with poor vision were recruited from an anti-VEGF injection clinic for treatment of age-related macular degeneration (AMD), diabetic retinopathy, and retinal vein occlusion. Anti-VEGF agents included bevacizumab, ranibizumab, and aflibercept. Patients were screened for visual hallucinations, and visual acuity and contrast sensitivity were tested. Results: 122 patients (mean age 75.3 years) were screened in a period of 6 weeks. 49 were male (40.1%). Diagnoses included AMD (n=92; 75.4%), diabetic retinopathy (n=21; 17.2%), and retinal vein occlusion (n=17; 13.9%). The prevalence of Charles Bonnet syndrome was 6.6% (n=8). Hallucinations usually involved people, lasted only minutes, and were associated with dim lighting. Poor visual acuity (p=0.002) and contrast sensitivity (p=0.001) were associated with visual hallucinations. Conclusion: Patients who see an ophthalmologist for treatment of eye diseases may experience visual hallucinations. Thus, healthcare professionals can benefit from greater awareness of Charles Bonnet syndrome, as not all visual hallucinations are caused by mental illness.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".