Increased risk of leg motor restlessness but not RLS in early Parkinson disease
Bibliographic record
Abstract
OBJECTIVE: This study explores the risk and correlates of leg restlessness in drug-naive patients with Parkinson disease (PD) as compared to control subjects matched for age and gender. METHODS: A total of 200 drug-naive patients with early, unmedicated PD derived from a population-based incident cohort and 173 age- and gender-matched control subjects were assessed for leg restlessness by structured interviews, clinical examination, and blood samples. All subjects were Caucasian. Restless legs syndrome (RLS) was diagnosed according to the essential diagnostic criteria. RESULTS: More patients (81 of 200, 40.5%) than controls (31 of 173, 17.9%) reported leg restlessness (p < 0.001). Thirty-one (15.5%) of these patients with PD and 16 (9.2%) control subjects met RLS criteria (p = 0.07). A total of 21 (12.5%) patients and 12 (6.9%) controls with RLS remained after the exclusion of potential RLS mimics and 26 patients vs 10 control subjects with leg motor restlessness (LMR), leading to a relative risk for RLS of 1.76 (95% confidence interval [CI] 0.90-3.43, p = 0.089) and 2.84 for LMR (95% CI 1.43-5.61, p = 0.001) in PD. Except for increased sleep disturbances in patients with RLS and increased Montgomery and Åsberg Depression Rating Scale scores for patients with RLS or LMR there were no other major differences in relevant blood tests, motor or cognitive function between PD with and without RLS or LMR. CONCLUSION: LMR and not RLS occurs with a near 3-fold higher risk as compared to controls in early PD. The findings underline a need for more accurate assessments of RLS in PD and support the notion that RLS and PD are different entities.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".