Incident Cardiovascular Events and Death in Individuals With Restless Legs Syndrome or Periodic Limb Movements in Sleep: A Systematic Review
Bibliographic record
Abstract
Study Objectives: To systematically review the current evidence examining restless legs syndrome (RLS) and periodic limb movements in sleep (PLMS) as prognostic factors for all-cause mortality and incident cardiovascular events (CVE) in longitudinal studies published in the adult population. Methods: All English language studies (from 1947 to 2016) found through Medline and Embase, as well as bibliographies of identified articles, were considered eligible. Quality was evaluated using published guidelines. Results: Among 18 cohorts (reported in 13 manuscripts), 15 evaluated the association between RLS and incident CVE and/or all-cause mortality and 3 between PLMS and CVE and mortality. The follow-up periods ranged from 2 to 20 years. A significant relationship between RLS and CVE was reported in four cohorts with a greater risk suggested for severe RLS with longer duration and secondary forms of RLS. Although a significant association between RLS and all-cause mortality was reported in three cohorts, a meta-analysis we conducted of the four studies of highest quality found no association (pooled hazard ratio = 1.09, 95% confidence interval: 0.80-1.78). A positive association between PLMS and CVE and/or mortality was demonstrated in all included studies with a greater risk attributed to PLMS with arousals. Conclusions: The available evidence on RLS as a prognostic factor for incident CVE and all-cause mortality was limited and inconclusive; RLS duration, severity, and secondary manifestations may be important in understanding a possible relationship. Although very limited, the current evidence suggests that PLMS may be a prognostic factor for incident CVE and mortality.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".