Charles Bonnet syndrome in older adults with age-related macular degeneration: Its relationship to depression and mild cognitive impairment
Bibliographic record
Abstract
Older adults are prone to have multiple chronic health conditions. The purpose of this study was to investigate whether older adults with age-related macular degeneration (AMD) who experience Charles Bonnet syndrome (CBS) are at a higher risk of developing depression and mild cognitive impairment (MCI). A total of 42 participants (31 females, 11 males; age: 68–99 years, M = 85.5 years; visual acuity [VA] in the better eye ranging from 20/70 to 20/1200) diagnosed with AMD were recruited in a vision rehabilitation center. They completed the Montreal Cognitive Assessment (MoCA) in its blind version, the Geriatric Depression Scale, and responded to questions designed to determine whether they experienced visual hallucinations consistent with CBS. Participants were then categorized into whether or not they experienced CBS, were at risk of depression or were at risk of MCI. Participants in the group experiencing CBS did not statistically show a higher likelihood of developing depression and/or MCI than those without CBS. Overall, the risk of depression (30%) was consistent with previous studies. In our sample of 42 older adults with visual impairment, 62% failed the MoCA suggesting they were at risk of cognitive decline. Our study was not able to replicate previous reports of a possible relationship between CBS and MCI in older adults with AMD; however, the observed level of possible cognitive impairment warrants further investigation. Future studies should include participants with other ocular pathologies to investigate whether a relationship among CBS, MCI, and/or depression may exist independently of AMD.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".