VITAMIN D AND PHYSIOPATHOLOGY OF UTERINE LEIOMYOMAS: SYSTEMATIC REVIEW IN ANIMAL MODELS, IN VITRO STUDIES AND CLINICAL OBSERVATIONS
Bibliographic record
Abstract
Background: Fibroids are benign tumors in women of reproductive age and associated with hormonal, genetic and molecular variables. Objectives: To search for the mechanisms by which vitamin D influences the development of fibroids. Search strategy: Electronic databases were searched from January 2009 to October 2019. The Internet search tool includes the PUBMED, COCHRANE and EMBASE search engines. Of these, scientific articles, meta-analyses, therapeutic guidelines, reviews, and research articles were consulted, as well as the most recent guidelines on the subject, according to the Brazilian Society of Gynecology. Selection criteria: The inclusion criteria were publications in the last ten years in English, Portuguese, and Spanish; publications that met the proposed objective described in PICO: a. Randomized trials; B. Observational studies (including cohort and case-control studies). Exclusion criteria included: articles published before 2010; languages other than English, Portuguese, and Spanish; articles that did not meet the research objectives; ongoing studies and abstracts. Data collection and analysis: The selected studies were divided according to the type of study and divided into: 1. Newcastle-Ottawa Scale-Case-Control Studies and Cohort Studies; 2. COCHRANE manual for systematic intervention reviews. Main results: 12 out of 15 studies were non-randomized studies (80%) with Kappa values above six. Kappa agreement was 0.615, suggesting good or substantial agreement. Conclusion: Vitamin D (1,25(OH)2 D3) plays a significant role in cell growth control, programmed cell death, and DNA damage. Low levels of Vitamin D seem to be an important factor, direct or indirectly, in the etiopathogenesis of uterine fibroids.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".