Association of Homocysteine Levels with Recurrent Pregnancy Loss: A Systematic Review
Bibliographic record
Abstract
Elevated homocysteine (Hcy) has been implicated in placental vascular dysfunction and adverse reproductive outcomes. Objective: To synthesize recent evidence on the association between Hcy levels and recurrent pregnancy loss (RPL), emphasizing methodological consistency and potential modifiers. Methods: Following PRISMA 2020, observational studies comparing Hcy in women with RPL versus controls were screened across PubMed, Scopus, and Cochrane. Reviews, pilots, case reports, abstracts, animal studies, and articles without quantitative Hcy data were excluded. Risk of bias was assessed using the Newcastle–Ottawa criteria; results were summarized with Synthesis Without Meta-analysis (SWiM). Results: Fourteen eligible studies across South Asia, the Middle East, Europe, and East Asia consistently reported higher Hcy among RPL cases, with typical mean differences =4–7 µmol/L and odds ratios ≈2–3, including studies adjusting for folate/B12 and MTHFR genotype. Heterogeneity stemmed from biospecimen type (serum/plasma), assay platform (HPLC vs immunoassay), fasting status, sampling time (preconception vs early pregnancy), and cut-offs (10–15 µmol/L). Emerging literature outside the included set supports endothelial mechanisms and gene nutrient interactions while highlighting reporting gaps and the need for interventional trials. Conclusions: Current evidence supports Hcy as a reproducible risk marker for RPL, plausibly mediated by endothelial and thrombo-inflammatory pathways and modified (but not fully explained) by folate/B12 status and genetic variants. Standardized measurement, rigorous adjustment, and randomized trials of targeted vitamin strategies are priorities.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| 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".