MétaCan
Menu
Back to cohort

Results of the Newcastle-Ottawa scale assessment.

2025· article· en· W6942288399 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typearticle
Languageen
FieldMedicine
TopicRestless Legs Syndrome Research
Canadian institutionsnot available
Fundersnot available
KeywordsPathogenesisVitaminVitamin B12Vitamin D and neurologyRandomized controlled trialVitamin CDisease

Abstract

fetched live from OpenAlex

<div> We performed a meta-analysis to assess the role of vitamins in the possible pathogenesis and treatment of RLS (Restless Leg Syndrome). A systematic search of the PubMed, Cochrane, Embase, and Web of Science databases was conducted. Fifty-nine studies on the relationship between vitamins and RLS were included, as well as four randomized controlled trials (RCTs) on vitamin treatment of RLS. Compared with non-RLS patients, serum vitamin D levels were significantly lower both in primary (P = 0.009) and secondary (P = 0.003) RLS patients, and appeared to be positively correlated with disease severity. Serum folate levels were lower in pregnant RLS patients than in pregnant non-RLS patients (P = 0.007), but this phenomenon was not seen in non-pregnant RLS patients (P = 0.65). Vitamin B12 (P = 0.59) and B1 (P = 0.362) deficiencies were not found in RLS patients. Oral vitamin B6 significantly improved primary RLS (P < 0.0001), while vitamin D did not (P = 0.05). Oral vitamin C (P < 0.00001), E (P < 0.0001), and vitamin C + E (P < 0.00001) all significantly improved hemodialysis-associated RLS with equal efficacy. Vitamin C is equivalent to 0.18 mg of pramipexole for the treatment of RLS (P = 0.81). In this meta-analysis, low vitamin D levels were found in patients with RLS, low folate levels were associated with RLS only in pregnant women, and vitamin C/E/B6 may improved symptoms in patients with RLS. These results suggest that vitamin deficiency or insufficiency may be related to the pathogenesis of RLS. </div>

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0300.000

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 head0.056
GPT teacher head0.392
Teacher spread0.336 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueFigshareSame topicRestless Legs Syndrome ResearchFrench-language works237,207