Characterization of painful Restless Legs Syndrome sensations in an English-speaking South African population
Bibliographic record
Abstract
Background and aims Restless Legs Syndrome (RLS) is characterised by unusual sensations in the legs which can be described as painful in up to 60% of RLS patients. The purpose of this study was to characterise and examine whether the presence of pain influenced the words used to describe the sensations of RLS in an English speaking population. Methods RLS participants (n=55) were divided according to whether or not painful RLS sensations were reported upon questioning. They completed the McGill Pain Questionnaire (MPQ), the International Restless Legs Syndrome Severity Scale (IRLS) and selected descriptors from a list of previously published RLS terms. Results Thirty-five percent of the RLS patients had painful sensations. The participants with painful RLS had higher Pain Rating Index (PRI) scores [median (interquartile range) 21 (17-28) vs. 14 (7.5-21) p=0.0008] and IRLS scores [23 (17-28) vs. 18 (11.5-22.5) p=0.0175] than the participants with non-painful RLS. Patients with painful RLS symptoms selected more pain-related literature terms, chose significantly different words in eight of the MPQ subclasses (both sensory and affective) and selected more intense descriptors from certain MPQ subclasses than the non-painful RLS group. The terms that characterised painful RLS were "aching", "painful", "cramping" and "unbearable". Conclusions Descriptors of RLS sensations are changed by the presence of pain, which may indicate an aetiological difference in the patients who have painful RLS. Clinically, patients complaining of cramping and painful sensations may be diagnosed with a condition that mimics RLS. Thus, it is important that the most accurate set of descriptors for RLS are used to enable recognition of RLS and optimised treatment according to the RLS phenotype. Implications The diagnosis of RLS may be improved by overcoming language and cultural barriers and obtaining differential diagnostic terms for painful conditions mimicking RLS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".