Bibliographic record
Abstract
BACKGROUND: Restless legs syndrome (RLS) is a common neurological condition characterized by uncomfortable and unpleasant sensations in the legs that are relieved by movement. It is frequently idiopathic, sometimes associated with specific disorders such as malignancies. Because there is no study relevant to RLS in Multiple Myeloma (MM), we aimed to evaluate the frequency of RLS in MM patients during chemotherapy and examined the relationship between presence of RLS and depression and anxiety in these patients. METHODS: We enrolled a population of 62 adult MM patients for RLS features. RLS was ascertained in MM patients by both the presence of the four essential International RLS Study Group diagnostic criteria and neurological examination. The International RLS Study Group rating scale was used to measure RLS severity. Hospital Anxiety and Depression Scale (HADS) was used to evaluate the levels of depression and anxiety and Short Form-36 (SF-36) to evaluate health related quality of life (HRQOL). RESULTS: A total of 62 MM patients were evaluated. Among them 11 were identified by the screening questionnaire to meet the criteria for RLS (17.74%). MM patients with RLS had higher levels of depression (P < 0.01) and anxiety (P < 0.01) and poorer HRQOL compared with those without RLS. CONCLUSIONS: The frequency of RLS in MM patients is higher than that of expected in the general population. MM patients afflicted by RLS have significantly higher levels of depression, anxiety and poorer HRQOL. Recognition and treatment of RLS in MM patients may be an important target in clinical management and may improve overall health outcomes in these 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 | 0.000 | 0.001 |
| 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".