Sleep Laboratory Diagnosis of Restless Legs Syndrome
Bibliographic record
Abstract
Polysomnographic recordings and the Suggested Immobilization Test (SIT) are frequently used to support the clinical diagnosis of restless legs syndrome (RLS). The present study evaluated the discriminant power of 5 different parameters: (1) index of periodic leg movements during sleep (PLMS), (2) index of PLMS with an associated microarousal (PLMS-arousal), (3) index of PLM during nocturnal wakefulness (PLMW), (4) SIT PLM index and (5) mean subjective leg discomfort score during the SIT (SIT MDS) in 100 patients with idiopathic RLS and 50 healthy control subjects. Both groups differed significantly on each parameter studied. Furthermore, while the SIT PLM, the PLMS and the PLMS-arousal indices revealed a poor ability to discriminate patients from controls, the PLMW index and the MDS both showed high sensitivity (87 +/- 7 and 82 +/- 8, respectively) and specificity (80 +/- 11 and 84 +/- 10, respectively) for diagnosing RLS. The combination of these 2 parameters correctly classified 88% of all subjects with a sensitivity of 82% and a specificity of 100%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".