Fatigue in systemic lupus erythematosus: contributions of disordered sleep, sleepiness, and depression.
Bibliographic record
Abstract
OBJECTIVE: To clarify the role of sleep disorders, sleepiness, and depression in patients with systemic lupus erythematosus (SLE) who complain of disabling tiredness. METHODS: Patients with SLE (31 women, 4 men) with disabling tiredness were evaluated with the Epworth Sleepiness Scale (ESS) and overnight polysomnography, followed by daytime multiple sleep latency tests (MSLT) and the Beck Depression Inventory (BDI). Their polysomnography was compared with 17 healthy, asymptomatic controls. RESULTS: Polysomnography of the patients in comparison with healthy controls showed impaired sleep efficiency (p < 0.02), high arousal frequencies (p < 0.01), increased stage 1 sleep (p < 0.02), decreased stage 3/4 slow-wave sleep (p < 0.02), and a high percentage (77% of patients) with increased alpha-EEG non-REM sleep. In 23% of patients periodic limb movement (PLM) disorder was observed (mean PLM index 31.1 +/- 15); 26% of patients had obstructive sleep apnea (mean apnea/hypopnea index 19.3 +/- 10), and one patient had narcolepsy-cataplexy. Remarkably, 51% of patients were excessively sleepy on both the ESS and MSLT (mean sleep latency < 10 min). This excessive daytime sleepiness was not related to sleep restriction. There was no association between sleepiness and SLE disease features such as neuropsychiatric SLE, medications, fibromyalgia, or disease activity. As a whole, the study group reported mild to moderate depression (mean BDI = 15.8 +/- 9.9). Within the group, the sleepy patients had lower BDI scores than the non-sleepy patients (p < 0.02), and fewer of the sleepy patients were depressed (p < 0.04). CONCLUSION: Primary sleep disorders, sleepiness, and depression are common in tired SLE patients. Tiredness in SLE that is the result of excessive daytime sleepiness can be distinguished from tiredness of depression. Such distinctions will help identify appropriate treatment for tired patients with SLE.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".