Incidence, worsening and risk factors of daytime sleepiness in a population-based 5-year longitudinal study
Bibliographic record
Abstract
Excessive daytime sleepiness (EDS) is highly prevalent in the general population; however little is known about its evolution and predictors. Our objectives were to document its natural history, provide estimates of its prevalence, incidence and persistence rates, and to identify predictors of increased daytime sleepiness (DS) in a longitudinal community study of 2157 adults over 5 years. Participants completed postal assessment at baseline and at each yearly follow-up. DS was evaluated by the Epworth Sleepiness scale (ESS). At baseline, 33% reported EDS (ESS > 10) with 33% of them reported persistent EDS. Of those without EDS at baseline, 28% developed incident EDS (15% were persistent) and 31% increased DS (augmentation ≥4-points between two consecutive evaluations). Younger age and depression were independent predictors of incident EDS and DS increase while lower coffee consumption, smoking, insomnia, tiredness and chronic pain were associated with incident EDS, and living alone with DS increase only. Persistent vs transient EDS or DS showed association with poor general health including metabolic diseases. Thus, sleepiness fluctuated over time and it was predicted by common lifestyle and psychological factors potentially modifiable. However, persistent sleepiness was associated with chronic medical diseases thus highlighting a homogeneous group at risk requiring a dedicated management.
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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 | 0.000 |
| 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) | 0.000 | 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".