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Is there a higher risk of restless legs syndrome in peripheral neuropathy?

2008· article· en· W1974026331 on OpenAlexaff
Erin Hattan, Colin Chalk, Ronald B. Postuma

Bibliographic record

VenueNeurology · 2008
Typearticle
Languageen
FieldMedicine
TopicRestless Legs Syndrome Research
Canadian institutionsMontreal General Hospital
Fundersnot available
KeywordsMedicinePeripheral neuropathyRestless legs syndromeEtiologyInternal medicineExacerbationPolyneuropathyNeurological examinationCase-control studyNeurological disorderPediatricsGastroenterologySurgeryCentral nervous system diseaseDiabetes mellitusNeurologyEndocrinologyPsychiatry

Abstract

fetched live from OpenAlex

Objective: Associations between peripheral neuropathy and restless legs syndrome (RLS) have been described, but have not been consistently reproduced. If RLS prevalence is truly increased by neuropathy, this has important implications for RLS pathophysiology. Methods: In a case-control design, 245 patients with peripheral neuropathy and 245 age- and sex-matched controls were screened for RLS using a standardized phone questionnaire based on international RLS diagnostic criteria. All persons who answered yes to three of four criteria were considered screen-positive. All screen-positive patients underwent a confirmatory diagnostic evaluation by a movement disorders specialist blinded to the neuropathy status of the patient. RLS prevalence was calculated and compared using Fisher exact test. Results: A total of 65 (26.5%) patients with neuropathy screened positive compared to 25 (10.2%) controls (p < 0.0001). However, the diagnosis was confirmed in only 46% of screen-positive patients with neuropathy, vs 80% of controls (p = 0.005). Cramps and paresthesia without true diurnal variation or rest exacerbation were the commonest causes of false-positive screens. After diagnostic confirmation, the overall prevalence of RLS did not differ between neuropathy patients and controls (12.2% vs 8.2%, p = 0.14). However, when classified by etiology, RLS was found in 14/72 (19.4%) patients with hereditary neuropathy, a prevalence higher than found in controls (p = 0.016) and acquired neuropathy (9.2%, p = 0.033). Among patients with neuropathy, those with RLS more commonly had a family history of RLS (37% vs 15%, p = 0.007) and were younger (49.9 vs 61.4, p = 0.0003). Conclusions: Restless legs syndrome is more prevalent among patients with hereditary neuropathy, but not in those with acquired neuropathies. CIDP = chronic inflammatory demyelinating polyneuropathy; GBS = Guillain-Barré syndrome; HMSN = hereditary motor sensory neuropathy; HSAN = hereditary sensory and autonomic neuropathy; IRLSSG = International Restless Legs Study Group; MGUS = monoclonal gammopathy of uncertain significance; NCS = nerve conduction studies; PPV = positive predictive value; RLS = restless legs syndrome.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.000
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.044
GPT teacher head0.309
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations106
Published2008
Admission routes1
Has abstractyes

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