The Influence of Vitamin D Levels on IVF Outcomes: A Systematic Review
Bibliographic record
Abstract
Vitamin D has been implicated in reproductive health, with potential effects on in vitro fertilization (IVF) outcomes. However, existing evidence remains conflicting. This systematic review evaluates the association between vitamin D levels and IVF success, including embryo quality, clinical pregnancy, and live birth rates. A comprehensive search of PubMed, Web of Science, Scopus, and Embase was conducted following PRISMA guidelines. Thirty studies (randomized controlled trials, prospective/retrospective cohorts) were included after screening 1,393 records. Data on vitamin D status (deficient [<20 ng/mL], insufficient [20–29 ng/mL], sufficient [≥30 ng/mL]) and IVF outcomes were extracted and qualitatively synthesized. Risk of bias was assessed using the Newcastle-Ottawa Scale and Cochrane tools. Findings were heterogeneous. Some studies reported improved embryo quality (e.g., higher blastocyst formation) and pregnancy rates with sufficient vitamin D (e.g., ≥30 ng/mL), particularly in women with polycystic ovary syndrome (PCOS) or thyroid autoimmunity. However, others found no significant association, including a large RCT showing no benefit from supplementation. Live birth rates were lower in deficient women in two studies (7.1% vs. 46%). Subgroup analyses highlighted variability by age, BMI, and genetic factors (e.g., VDR polymorphisms). While vitamin D sufficiency may enhance certain IVF outcomes, evidence is inconsistent, and optimal thresholds remain unclear. Routine supplementation cannot yet be universally recommended, but screening for deficiency appears prudent. Future research should prioritize standardized measurements and large RCTs focusing on live birth rates.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.009 | 0.010 |
| 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) | 0.005 | 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".