Gut Microbiota and Oral Contraceptive Use in Women with Polycystic Ovary Syndrome: A Systematic Review
Bibliographic record
Abstract
Background: Polycystic ovary syndrome (PCOS) is one of the most prevalent endocrine syndromes affecting women at reproductive age. With increasing knowledge of the role of the microbiota in the pathogenesis of PCOS, new management strategies began to emerge. However, data on the impact of established treatment regimens, such as metformin and oral contraceptive agents, on the gut microbiota composition are scarce. This study aimed to evaluate the specificity of the gut microbiota in women with PCOS before and after treatment with oral contraceptives. Methods: We have systematically searched the following databases: PubMed/MEDLINE, Scopus, Web of Science and Google Scholar. The last search was performed on 13 May 2024. We included only full-text original research articles written in English. The risk of bias was assessed using a modified version of the Newcastle–Ottawa Scale. Results: The above described search strategy retrieved 46 articles. Additionally, 136 articles were identified and screened through Google Scholar. After removing duplicates, we screened the titles and abstracts, resulting in three eligible articles constituting the final pool. They were published between 2020 and 2022 and are based on three ethnically distinct study populations: Turkish, Spanish and American. The studies included a total of 37 women diagnosed with PCOS and using OCs. Conclusions: OC treatment does not seem to affect the gut microbiota in a significant way in patients with PCOS in short observation. Well-designed randomized controlled studies with adequate, unified sample size are lacking.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".