Vitamin D receptor (VDR) gene polymorphisms and risk for polycystic ovary syndrome and infertility: An updated systematic review and meta-analysis
Bibliographic record
Abstract
Background: Vitamin D receptor (VDR) gene polymorphisms have been implicated in polycystic ovary syndrome (PCOS). Despite VDR gene polymorphisms importance and their risk for PCOS, they have not been extensively studied. The main objective was to evaluate the associations between VDR gene polymorphisms and risk for PCOS. Methods: The current systematic review and meta-analysis examined VDR gene polymorphisms with PCOS in case-control and cohort studies. Relevant keywords were used to search Scopus, Web of Science, PubMed, MEDLINE, ScienceDirect, and Google Scholar for peer-reviewed publications until July 1, 2024. Selected papers were assessed for risk bias and quality using the Modified Newcastle-Ottawa scale. A meta-analysis was conducted using a random-effect model. The association between VDR gene polymorphism(s) and PCOS in women was reported as odds ratios (ORs) with 95 % confidence intervals (CIs). Results: ) polymorphism with PCOS risk. Conclusions: I VDR gene polymorphisms may have a higher risk of PCOS. This study was registered on the Prospective International Registry of Systematic Reviews (PROSPERO) with registration number CRD42024564851.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.026 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".