Vitamin D and Sjögren’s Disease: Revealing the Connections—A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: The aim of the present review was to summarize the current evidence about the impact of vitamin D deficiency on pathology and clinical manifestations of Sjögren’s disease (SD). Methods: Databases PubMed, Web of Science, Scopus, and Cochrane library were searched for studies assessing the levels of vitamin D in SD patients using the following keywords: (vitamin D OR calciferol OR cholecalciferol OR 25-hydroxyvitamin D OR 25-hydroxycholecalciferol OR calcidiol OR calcitriol OR 1,25-dihydroxycholecalciferol) AND (Sjögren’s Syndrome OR Sjögren’s disease) accessed on 20 September 2022. Out of 248 retrieved studies, following the systematic review methodology and defined inclusion and exclusion criteria, 9 clinical studies were eligible to be included in the present review: 4 of them case-control, 4 cross-sectional, and 1 cohort study. Results: Nine studies totaling 670 SD patients and 857 healthy controls were eligible for meta-analysis with moderate to high methodological quality as determined by the Newcastle–Ottawa Quality Scale (NOS). According to the obtained results, a high prevalence of hypovitaminosis D was observed in SD patients when compared to healthy controls (95% CI −10.43, −2.39; p < 0.01). Conclusion: Available evidence points to lower levels of vitamin D in patients with SD in comparison to healthy controls. However, further studies are necessary to understand the underlying mechanisms associated with the role of vitamin D in the development and disease severity of SD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".