Restless leg syndrome: a risk factor of higher prevalence of anxiety and depression in Parkinson’s disease patients
Bibliographic record
Abstract
BACKGROUND: Many studies have assessed the relationship of depression and anxiety with Parkinson's disease (PD), as well as examining restless leg syndrome (RLS) with depression and anxiety. Nonetheless, there has not been an extensive effort to show how the prevalence of RLS affects both depression and anxiety in PD patients. The objective of this study was to examine how the prevalence of RLS in PD patients affects the prevalence and severity of depression and anxiety and how they compare with each other. This study is the first of its kind that examines the effects of the combination of the two neurological conditions with depression and anxiety as well as comparing their prevalence and severity to each other. METHODS: The study included 27 PD patients who also suffered from RLS, 27 PD patients not suffering from RLS, and 27 gender-matched healthy individuals. All were evaluated for caseness and severity of both anxiety and depression using the Hospital Anxiety and Depression Scale (HADS); HADS-A and HADS-D, respectively. RESULTS: PD patients with RLS reported having the highest prevalence of both anxiety and depression. The least reported cases for both anxiety and depression were in the control group. In comparison, the results for severity of anxiety and depression within the three groups showed that PD patients with and without RLS had significantly higher severity scores for both anxiety and depression than the control group, but the scores did not significantly differ between the two PD patient groups. CONCLUSION: The presence of RLS in PD patients may increase the occurrence of both anxiety and depression, but the severity of the symptoms is not significant in the two groups of the PD patients.
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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 | 0.000 |
| 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) | 0.002 | 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".