Restless Legs Syndrome in a Rheumatoid Arthritis Patient Cohort
Bibliographic record
Abstract
OBJECTIVE: To use the 2003 International Restless Legs Syndrome Study Group (IRLSSG) diagnostic criteria and to evaluate restless legs syndrome (RLS) prevalence in a rheumatoid arthritis (RA) and osteoarthritis (OA) population. Further, we wished to evaluate physician awareness of this disorder by as reflected in prevalence of preexisting diagnoses of RLS in these populations. METHODS: This was a questionnaire study of Saskatchewan RA and OA patients enrolled in a longitudinal database study. A data collection instrument, including the 2003 IRLSSG criteria for RLS was distributed to the patients enrolled. RESULTS: Of the 193 respondents, 158 (81.9%) were women. The population consisted of 148 RA and 45 OA patients. RA patients were younger (mean age, 65.8 years) in comparison with those in the OA group (mean age, 72.8 years; P < 0.001). All criteria for RLS were met by 27.7% of RA patients and by 24.4% of OA patients. A previous diagnosis of RLS was reported by 2.6% of patients. CONCLUSIONS: A quarter of all our patients met the 2003 IRLSSG criteria, in both RA and OA groups; however, only 2.6% of study patients reported a previous diagnosis of RLS. As RLS can significantly affect quality of life, increased awareness with improvement in surveillance, recognition, and treatment would be beneficial to patient care. We advocate screening for symptoms of sleep disorders to be incorporated into the routine rheumatologic history for all patients with RA and OA.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".