Vitamin D and biomarkers of inflammation and oxidative stress among pregnant women: a systematic review of observational studies
Bibliographic record
Abstract
OBJECTIVE: This systematic review aimed to map the evidence evaluated the relationship between vitamin D and redox and inflammatory status during gestation. METHODS: Three databases (PubMed/MEDLINE, Scopus, and Web of Science (WoS)) and reference list of included documents were searched for related observational studies published until 2nd October 2023. To determine the quality of the selected observational studies, the Newcastle-Ottawa Scale (NOS) was used. RESULTS: After a primary search of three databases, 19492records were appeared. When duplicates and irrelevant documents were removed, 14 articles were found to have eligible criteria. The design of the identified studies was cross-sectional, case-control and cohort. Evidence showed an adverse association between 25(OH)D and the biomarkers of inflammation, such as high-sensitivity C-reactive protein (hs-CRP), Interleukin-1beta (IL-1β), Interleukin-6 (IL-6), and tumor necrosis factor- alfa (TNF-α) during pregnancy. On the contrary, some studies represented that 25(OH)D positively correlated with hs-CRP in the cord blood. One study suggested a direct association between serum concentrations of 25(OH)D and Interleukin-8 (IL-8), macrophage inflammatory protein (MIP), and TNF-α levels in mothers with gestational diabetes mellitus (GDM). A case-control study showed that lower serum concentration of 25(OH)D positively correlated with total antioxidant capacity (TAC) levels in participants. CONCLUSIONS: Evidence confirmed the supposition of the direct relationship between vitamin D levels and biomarkers with anti-inflammatory and anti-oxidative properties. However, the Existence of inconsistent evidence confirms the need for further studies in mothers with GDM and hypertensive disorders. PROSPERO REGISTRATION CODE: CRD42020202600.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".