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VITAMIN D LEVEL IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS AND ITS ASSOCIATION WITH BONE TURNOVER MARKERS

2025· article· en· W4410715482 on OpenAlexvenueno aff
Tetiana Malovana, S. Shevchuk

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBone remodelingVitamin D and neurologyInternal medicineSystemic diseaseAssociation (psychology)Lupus erythematosusVitaminImmunologyImmunopathologyAntibody

Abstract

fetched live from OpenAlex

PV028 / #749 Poster Topic: AS04 - Biomarkers Background/Purpose According to scientific sources, vitamin D insufficiency has been detected in two-thirds of patients with systemic lupus erythematosus (SLE), while the deficiency is observed in 1 of 5 individuals. Hypovitaminosis D in SLE patients can be caused by kidney damage, chronic administration of glucocorticoids and, possibly, hydroxychloroquine, use of sunscreens, formation of antibodies to vitamin D, etc. It is also known that SLE patients demonstrate a tendency to rapid bone loss caused by impaired differentiation and decreased activity of osteoblasts, increased maturation and activity of osteoclasts, and accelerated apoptosis of osteocytes in chronic inflammations. Here, serum bone turnover markers may play a role in assessing synthesis and resorption progress. At the same time, the information about vitamin D influencing bone metabolism requires further study. The study is intended to determine vitamin D levels in SLE patients and assess their relationship with bone turnover markers. Methods We examined 65 SLE patients (mean age 48.95±1.46 years) and 30 the control group subjects of the corresponding age and sex. The main group consisted of 54 (83.08%) women and 11 (16.92%) men. The average duration of the disease was 12.05±1.09 years. We used ELISA to determine vitamin D concentration and characterized it as optimal (30–50 ng/ ml), insufficient (20–30 ng/ml) and deficient one (<20 ng/ml). The blood serum osteocalcin, procollagen type I C-terminal propeptide and C-terminal telopeptide of type I collagen were determined using ELISA. Results Blood serum vitamin D concentration in SLE patients was 18.58±0.97 ng/ml, while the one in the control group subjects was 27.44±1.28 ng/ml. Vitamin D deficiency and insufficiency was diagnosed in 43 (66.15%) and 16 (24.62%) patients, respectively, while only 6 (9.23%) subjects had the optimal vitamin D level. The control group presented normal 25(OH)D concentration, vitamin D insufficiency, and deficiency in 11 (36.67%), 11 (36.67%), and 8 (26.66%) subjects, respectively. Vitamin D levels were associated with the metabolic state of bone tissue, as indicated by a proportional change in the concentration of synthesis markers, such as osteocalcin (OC), procollagen type I C-terminal propeptide (PICP) and a resorption marker, C-terminal telopeptide of type I collagen (CTX). For example, patients with vitamin D deficiency had average OC and PICP 21.45% and 25.72% lower, accordingly, than had the patients of the group with optimal vitamin D concentration (p < 0.05). The average CTX in patients with vitamin D deficiency was 38.71% higher than the one in the group of patients that presented no hypovitaminosis D (p < 0.01). The results of the correlation analysis confirmed the close relationship between the vitamin D concentration and OC (r = 0.32; p = 0.01), and CTX (r = -0.25; p < 0.05). A reliable direct correlation was also established between CTX and the total dose of glucocorticoids (r = 0.48; p < 0.001). Conclusions Our study has demonstrated a significant prevalence of vitamin D deficiency and insufficiency in the Ukrainian population of SLE patients, as well as close association of hypovitaminosis D with changes in bone turnover markers (OC, PICP, CTX).

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 score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.248
Teacher spread0.237 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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