Sleep Problems in Patients with Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To investigate sleep problems, and the relationship between sleep and disease activity, in Belgian patients with established rheumatoid arthritis (RA). METHODS: This cross-sectional, observational, multicenter study assessed sleep quality using the Athens Insomnia Scale (AIS) and Pittsburgh Sleep Quality Index (PSQI), and daytime sleepiness using the Epworth Sleepiness Scale (ESS). Additional patient-reported outcomes included visual analog scales (VAS) for fatigue and pain, the Medical Outcomes Study Short Form-36 Health Survey, the Health Assessment Questionnaire-Disability Index (HAQ-DI), and the Positive and Negative Affect Schedule. Multivariate regression and structural equation modeling identified factors associated with sleep quality, with the 28-joint Disease Activity Score [DAS28-C-reactive protein (CRP)] as a continuous or categorical variable. Analyses were performed on the total population and on patients stratified by disease activity status: remission/low (DAS28-CRP ≤ 3.2) or moderate to high (DAS28-CRP > 3.2). RESULTS: Among 305 patients, mean (SD) age was 57.00 (12.38) years and mean (SD) disease duration was 11.77 (9.94) years. Mean (SD) AIS, PSQI, and ESS scores were 6.8 (4.79), 7.8 (4.30), and 7.3 (4.67), respectively. Mean (SD) VAS fatigue, VAS pain, and HAQ-DI were 45.22 (26.29), 39.04 (26.21), and 1.08 (0.75), respectively. There were significant positive relationships between DAS28-CRP and AIS/PSQI, but a significant negative relationship between DAS28-CRP and ESS. Several potentially confounding factors were identified. CONCLUSIONS: Poor control of RA is associated with a reduction in sleep quality and decreased daytime sleepiness, which is likely explained by pain-related alertness. Future prospective studies are needed to confirm potential relationships between sleep quality, sleepiness, and RA treatment.
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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 | 0.001 |
| 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".