Retinal Disorders and Sleep Disorders: Are They Genetically Related?
Bibliographic record
Abstract
Introduction Sleep is important for optimal physical health and vitality. Recent studies have shown that individuals with visual impairments may be at risk for sleep problems. This research examines the prevalence of sleep problems among those with retinal disorders and the possibility of a genetic link. Methods Subjects with retinitis pigmentosa ( n = 33), Stargardt's disease ( n = 31) and age-related macular degeneration ( n = 43) were recruited from the ophthalmology department of Montreal Children's Hospital. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS). Genetic testing was conducted by the Radboud University Medical Center in Nijmegen, Netherlands. Retinal genes were identified as having retina only or pineal and retinal expression. Results The expression patterns of genes causing retinal disorders did not predict sleep quality. The PSQI indicated poor sleep quality in 56% of participants with retinitis pigmentosa, 48% of those with Stargardt's disease, and 53% of those with age-related macular degeneration. The ESS showed that daytime sleepiness was experienced by 20% of individuals with retinitis pigmentosa or Stargardt's disease, and by only one individual with age-related macular degeneration. Discussion Approximately 50% of people with retinal disease have sleep problems. This number compares with up to one-third of the general population. Gene expression did not correlate with sleep quality, and the explanation for such a large percentage of sleep disorders needs further investigation. Implications for practitioners Eye care and rehabilitation specialists need to be aware of the high prevalence of poor sleep quality in individuals with retinal disorders, since this situation may have an important impact on memory and learning, both of which are vital in successful rehabilitation.
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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) | 0.000 | 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 | 0.001 |
| 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".