A systematic review and meta-analysis of the correlation between polycystic ovary syndrome and irritable bowel syndrome
Bibliographic record
Abstract
Background Research on the prevalence of irritable bowel syndrome (IBS) among polycystic ovary syndrome (PCOS) patients has gained significant momentum over the years. However, it remains unclear whether PCOS is related to a higher prevalence of IBS. The objective of this systematic review and meta-analysis was to fully study IBS correlation with PCOS.Methods From inception until October 16th, 2022, all observational studies documenting IBS prevalence in PCOS patients were collected from the China national knowledge infrastructure(CNKI), China Science and Technology Journal Database(VIP), Wanfang database, PubMed, Embase, Web of Science, and Cochrane databases. The quality of case-control studies was assessed with Newcastle-Ottawa Scale. Review Manager 5.3 was used to determine the pooled odds ratio (OR) and 95% confidence interval (CI).Results 5 case-control studies involving 1268 individuals and one cross-sectional study involving 291 participants were included in our qualitative analysis. The quantitative analysis was conducted based on five case-control studies. Four case-control studies involving 1063 participants showed a higher prevalence of IBS in PCOS This meta-analysis revealed an almost twice higher risk of IBS in comparison with controls (OR = 2.23, 95%CI:1.58-3.14, p < 0.001; I2=41%, p = 0.150). Four sensitivity analyses validated the consistency of the aggregated findings.Conclusion This meta-analysis and systematic review demonstrated a significant association between PCOS and increased odds of IBS. However, more high-quality and well-controlled research is essential to increase the robustness of our conclusions.
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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 | 0.018 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.027 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".