Systemic Lupus and Risk of Restless Legs Syndrome
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of restless legs syndrome (RLS) in women with systemic lupus erythematosus (SLE), and to compare this to a rheumatic disease sample without SLE. METHODS: Unselected consecutive female patients were SLE were recruited from a lupus clinic. A RLS questionnaire based on 4 criteria, validated by the International Restless Legs Syndrome Study Group, was administered during a face-to-face interview. Smoking history and height and weight data were collected. Similar methods were used to determine RLS prevalence in a comparator group of women with rheumatic diseases other than SLE. Controls were frequency-matched by age group (in 5-year age bands) to SLE subjects. Controls were otherwise unselected. RESULTS: We recruited 33 women with SLE and 32 controls. Twelve of 33 female SLE subjects scored positively for RLS (37.5%; 95% CI 22.9, 54.7) compared to 4 of 32 controls (12.5%; 95% CI 5.0, 28.1). Multivariate logistic regression showed that adjusted for age, obesity, and smoking, women with SLE were more likely to have RLS than the female controls (adjusted odds ratio 6.61, 95% CI 1.52, 28.77). In our multivariate analyses of all rheumatic patients, including SLE, the adjusted OR for obesity and RLS was 5.14 (95% CI 1.07, 24.6). CONCLUSION: These novel data indicate that RLS is more prevalent in women with SLE than in controls. Although obesity was a significant risk factor for RLS in our sample, the predictive covariates examined were limited.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 it