Sleep and Sleep Complaints in Juvenile Fibromyalgia Syndrome
Bibliographic record
Abstract
Objective To investigate sleep quality in juvenile fibromyalgia syndrome (JFS) and its effect on the global burden of the disease. Methods Consecutive patients with JFS who performed full-night polysomnography (PSG) were included in this cross-sectional study. JFS-related symptoms, neuropsychiatric features, and sleep quality were assessed using self-report measures. PSG sleep parameters, including N3 distribution index, were obtained from patients and age-matched healthy controls. Results We included 25 patients (20 females, median age 15.7 yrs). Nonrestorative sleep was reported by 22 of 25 (88%) patients. Patients with JFS showed significantly longer sleep period time (P= 0.004) and increased wake after sleep onset (P= 0.03) compared to healthy peers. The N3 distribution index was significantly lower in patients than in the control group (P= 0.02). Subjective poor sleep quality was related to Widespread Pain Index (WPI;rs−0.65), Symptom Severity Scale (rs−0.64), depressive symptoms (rs−0.58), fatigue (rs−0.44), and symptom severity upon awakening (rs−0.65). The N3 distribution index was correlated to depressive symptoms (rs0.41) and irritability (rs0.40). On multiple regression analysis, WPI was predicted by subjective sleep quality (β −0.32,P= 0.04), whereas depressive symptoms were predicted by subjective sleep measures (β −0.32,P= 0.04) and PSG parameters (N3 min: β −0.07,P= 0.03). Conclusion Sleep complaints are a key hallmark of JFS and have significant effect on relevant clinical domains of the disease, such as pain and depression.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".