Follicular fluid composition and reproductive outcomes of women with polycystic ovary syndrome undergoing in vitro fertilization: A systematic review
Bibliographic record
Abstract
Polycystic ovary syndrome (PCOS) is recognized as one of the most prevalent endocrinopathy in women at reproductive age. As affected women tend to have poorer assisted reproductive technology (ART) outcomes, PCOS has been suggested to endanger oocyte quality and competence development. The aim of this systematic review was to summarize the available evidence on how the follicular fluid (FF) profile of women with PCOS undergoing in vitro fertilization (IVF) treatment differs from the FF of normo-ovulatory women. For that, an electronic search in PubMed and Web of Science databases was conducted (up to December 2021). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses - PRISMA guidelines were followed, and the Newcastle-Ottawa Scale was used to assess the risk of bias in the included studies. Data retrieved from papers included (n=42), revealed that the FF composition of women with PCOS compared to those without PCOS predominantly diverged at the following molecular classes: oxidative stress, inflammatory biomarkers, growth factors and hormones. Among those biomarkers, some were proposed as being closely related to pathophysiological processes, strengthening the hypothesis that low-grade inflammation and oxidative stress play a critical role in the pathogenesis of PCOS. Notwithstanding, it should be noticed that the available data on PCOS FF fingerprints derives from a limited number of studies conducted in a relatively small number of subjects. Furthermore, phenotypic heterogeneity of PCOS hampers wider comparisons and weakens putative conclusions. Therefore, future studies should be focused at comparing well characterized patient subgroups according to phenotypes.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".