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Record W7043939921

Vitamin D status in symptomatic knee osteoarthritis: Association with clinical and radiographical parameters

2014· article· en· W7043939921 on OpenAlexaboutno aff

Bibliographic record

VenueDergiPark (Istanbul University) · 2014
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACOsteoarthritisVitamin D and neurologyvitamin D deficiencyBody mass indexVitamin
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: We aimed to examine the relationship between vitamin D deficiency and knee osteoarthritis in women aged 45-60. METHODS: 110 female patients with knee osteoarthritis were included. Patients were divided into two groups according to vitamin D level: group 1 included 65 patients with low vitamin D (< 20 ng/ml), and group 2 included 45 patients with vitamin D in normal ranges (≥20 ng/ml). Severity of osteoarthritis was evaluated by Kellgren-Lawrence (KL). Pain, stiffness and functional status were measured by Western Ontario and McMasters Universities Osteoarthritis Index (WOMAC). RESULTS: Rate of vitamin D deficiency was 59.09%. Mean vitamin D level was 9.09±3.82 in group 1 and 27.84±6.42 in group 2. Vitamin D was significantly lower in group 1 (p=0.00). K/L grade 1(28.89%) and 2(64.44%) were most frequently found in group 2, whereas grade 3(38.46%) and 4(15.38%) were found in group 1. Group1 had significantly higher radiographic grades than group 2 (p=0.00). Patients in group 1 scored significantly higher in WOMAC (p=0.00). K/L scores were correlated with VAS-pain and WOMAC scores (p=0.00). K/L scores showed no significant correlation with body mass index (BMI) (p=0.82).CONCLUSION: Vitamin D deficiency is associated with knee OA in terms of pain, stiffness, functional and radiological status.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.246
Teacher spread0.236 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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