SYSTEMATIC REVIEW OF THE ASSOCIATION BETWEEN VAGINAL MICROBIOME COMPOSITION AND THE SUCCESS OF FROZEN EMBRYO TRANSFER
Bibliographic record
Abstract
Background: Infertility remains a significant global health burden, with frozen embryo transfer (FET) constituting an increasingly prevalent and successful assisted reproductive technology. Despite advancements, implantation failure persists, prompting investigation into the endometrial microenvironment. The vaginal microbiome is a dynamic component of this environment, yet its specific association with FET outcomes remains inconsistently reported, necessitating a systematic synthesis of the evidence. Objective: This systematic review aims to synthesize the available evidence linking specific vaginal microbiome compositions to implantation and clinical pregnancy rates in individuals undergoing frozen embryo transfer. Methods: Following PRISMA guidelines, a comprehensive search of PubMed/MEDLINE, Scopus, Cochrane Library, and Web of Science was conducted for observational studies published between 2014-2024. Eligible studies reported on vaginal microbiome composition prior to or during an FET cycle and its association with reproductive outcomes. Two independent reviewers performed study selection, data extraction, and quality assessment using the Newcastle-Ottawa Scale. Results: Eight observational studies (n=1,347 participants) were included. A key finding was methodological divergence: studies using molecular sequencing (16S rRNA) consistently associated a Lactobacillus-dominant microbiome, particularly with L. crispatus, with significantly higher clinical pregnancy rates. Conversely, studies utilizing Nugent scoring found no significant association between bacterial vaginosis-defined dysbiosis and FET outcomes. Conclusion: The association between vaginal microbiome and FET success appears contingent on assessment methodology. An optimal microbiome, characterized by specific beneficial lactobacilli, may support implantation, whereas traditional diagnostic criteria lack sensitivity for this predictive role. Current evidence, while promising, is observational and heterogeneous. Future research requires standardized molecular methodologies and randomized controlled trials to explore causal relationships and therapeutic modulation.
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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 | 0.010 | 0.061 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".