The electroretinography to identify biomarkers of idiopathic hypersomnia and narcolepsy type 1
Bibliographic record
Abstract
Hypersomnia spectrum disorders are underdiagnosed and poorly treated due to their heterogeneity and absence of biomarkers. The electroretinography has been proposed as a proxy of central dysfunction and has proved to be valuable to differentiate certain psychiatric disorders. Hypersomnolence is a shared core feature in central hypersomnia and psychiatric disorders. We therefore aimed to identify biomarkers by studying the electroretinography profile in patients with narcolepsy type 1, idiopathic hypersomnia and in controls. Cone, rod and retinal ganglion cells electrical activity were recorded with flash-electroretinography in non-dilated eye of 31 patients with idiopathic hypersomnia (women 84%, 26.6 ± 5.9 years), 19 patients with narcolepsy type 1 (women 63%, 36.6 ± 12.7 years) and 43 controls (women 58%, 30.6 ± 9.3 years). Reduced cone a-wave amplitude (p = 0.039) and prolonged cone (p = 0.022) and rod b-wave (p = 0.009) latencies were observed in patients with narcolepsy type 1 as compared with controls, while prolonged photopic negative response-wave latency (retinal ganglion cells activity) was observed in patients with idiopathic hypersomnia as compared with controls (p = 0.033). The rod and cone b-wave latency clearly distinguished narcolepsy type 1 from idiopathic hypersomnia and controls (area under the curve > 0.70), and the photopic negative response-wave latency distinguished idiopathic hypersomnia and narcolepsy type 1 from controls with an area under the curve > 0.68. This first original study shows electroretinography anomalies observed in patients with hypersomnia. Narcolepsy type 1 is associated with impaired cone and rod responses, whereas idiopathic hypersomnia is associated with impaired retinal ganglion cells response, suggesting different phototransduction alterations in both hypersomnias. Although these results need to be confirmed with a larger sample size, the electroretinography may be a promising tool for clinicians to differentiate hypersomnia subtypes.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".