Month of Birth as a Risk Factor for Narcolepsy
Bibliographic record
Abstract
STUDY OBJECTIVES: A loss of hypocretin neurons has been observed in human narcolepsy; however, the cause of this disorder is still unknown. While family history and genetic factors are important individual risk factors for narcolepsy, environmental factors also contribute to the pathogenesis of the disease. The aim of the study was to find out whether there is a seasonality of month of birth in narcoleptic patients. DESIGN: Diagnosis of narcolepsy with cataplexy was based on International Classification of Sleep Disorders criteria with clinical, standard polysomnographic, and Multiple Sleep Latency Test features. PATIENTS AND SETTING: The birth dates of 886 patients with a clear-cut diagnosis of narcolepsy with cataplexy from 3 large narcolepsy databases (352 from Montpellier-France, 157 from Montreal-Canada, and 377 from Stanford-United States of America) were compared with those of 35,160,522 subjects from the general population. MEASUREMENTS AND RESULTS: Patients with narcolepsy had a significantly different seasonality of month of birth compared to that of the general population. The monthly distribution of birth yielded a peak in March with a maximal odds ratio at 1.45 and a trough in September with a minimal odds ratio at 0.63. No gender or country of origin differences were observed. CONCLUSIONS: A birth seasonality in the development of narcolepsy suggests the presence of environmental factors acting in combination with genetic factors during the fetal or perinatal period, in terms of an autoimmune process targeting the hypocretin system.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| 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 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".