Restless legs syndrome in patients on hemodialysis: Polysomnography findings
Bibliographic record
Abstract
Abstract Introduction: Restless legs syndrome (RLS) is a highly prevalent sleep movement disorder usually accompanied by periodic limb movements of sleep (PLMS). The incidence of RLS and PLMS in patients with end‐stage renal disease (ESRD) on dialysis is much higher. Clinically, RLS and PLMS can co‐occur. We hypothesized that patients with ESRD on dialysis would have a distinct presentation of RLS, with a higher prevalence of PLMS. Methods: We examined clinical, demographic, biochemical, and polysomnographic characteristics of RLS in patients on dialysis matched to control subjects with normal renal function based on age, sex, body mass index, and frequency of apneas and hypopneas per hour of sleep, defined by the apnea and hypopnea index (AHI), in a proportion of 3:1. Patients with ESRD were on hemodialysis three times per week. Polysomnography was performed overnight in the sleep laboratory. Findings: Patients on dialysis compared to control subjects had a lower amount of N3 sleep (77.6 ± 39.9 minutes vs. 94.8 ± 33.7 minutes, p = 0.037) and REM sleep (55.6 ± 27.5 minutes vs. 74.1 ± 28.4 minutes, p = 0.006), regardless of the presence of RLS. Among the patients on dialysis, those with RLS had higher PLMS. In the control group, patients with RLS had a lower ferritin level, which was not observed in the dialysis group. There was a significant interaction between PLMS and ESRD (p = 0.001), with a higher prevalence of PLMS in patients with ESRD on dialysis in a model adjusted for AHI, sex, arousals, and age. Factors that were associated with PLMS were RLS (p = 0.003), ESRD (p = 0.0001), and AHI (p = 0.041), with an adjusted R2 of 0.321. Conclusion: RLS in patients with ESRD on dialysis is independently associated with PLMS, regardless of the severity of sleep apnea, arousals, and age.
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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 | 0.000 | 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 | 0.000 |
| 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".