Subjective fatigue and subjective sleepiness: two independent consequences of sleep disorders?
Bibliographic record
Abstract
The objective of this investigation was to evaluate subjective fatigue versus subjective sleepiness as independent consequences of sleep disorders. Furthermore, we tried to explore how these symptoms relate to alertness, depressive symptoms and illness intrusiveness. In a prospective observational study, 283 sleep-disordered patients referred to a hospital-based sleep laboratory for various indications over a 1-year period were evaluated vis-à-vis fatigue and sleepiness. All patients completed five subjective questionnaires, underwent objective sleep recording and attended a clinical interview with a sleep specialist. The subjective questionnaires included the Epworth Sleepiness Scale, the Fatigue Severity Scale, the Toronto Hospital Alertness Test, the Illness Intrusiveness Rating Scale and the Center for Epidemiologic Studies-Depression Scale. Only 4% of the total sample was referred to the sleep clinic due to a complaint of excessive fatigue compared with 17% for excessive daytime sleepiness. However, during the assessment, 64% of referred patients reported pathological fatigue without overlap of sleepiness and only 4% reported pathological sleepiness without overlap of fatigue. Pearson's correlation analysis indicated a weak association (r=0.18) between subjective fatigue and sleepiness in the total sample. Analysis of variance testing showed strong association between those patients with prominent fatigue and depressive symptoms (P<0.01) and illness intrusiveness (P<0.001). The findings support the notion that subjective fatigue and sleepiness can be independent manifestations of sleep disorders. Furthermore, predominantly fatigued individuals with sleep disorders seem vulnerable to additional negative consequences due to possible interplay between amplified fatigue and psychological distress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".