Case Report: Effect of a Retinal Prosthesis System on Charles Bonnet Visual Hallucinations
Bibliographic record
Abstract
SIGNIFICANCE: Charles Bonnet syndrome is commonly encountered and diagnosed in low-vision patients. It can be distressing for some of them, as there is no known effective treatment of this condition. Although there is a growing interest in retinal implants for blind patients with severe retinal diseases, the effect of these devices on Charles Bonnet syndrome visual hallucinations remains undocumented. PURPOSE: The aim of this study was to report changes in the Charles Bonnet syndrome of a patient with retinitis pigmentosa after implantation of the Argus II retinal prosthesis. CASE REPORT: A 65-year-old patient with retinitis pigmentosa and no light perception was frequently experiencing Charles Bonnet syndrome. In the hope of improving his vision, he received an Argus II retinal prosthesis in 2018 and participated in a 10-week rehabilitation program at the Institut Nazareth et Louis-Braille. The nature and the frequency of his Charles Bonnet syndrome were documented with the Questionnaire de repérage du syndrome de Charles Bonnet (a French questionnaire used to screen for Charles Bonnet syndrome) before the surgery and for 70 weeks after it. The patient's visual acuity and visual fields were monitored during the same period. Additional tests were administered to document the visual, psychological, and cognitive states of the patient throughout the study. CONCLUSIONS: Although this case report confirmed that Argus II retinal prosthesis improves the performance of blind patients in visual tests, the improvement was not associated with a decrease in the symptoms of Charles Bonnet syndrome.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 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".