Association between endometriosis and gut microbiota: systematic review and meta-analysis
Bibliographic record
Abstract
Background Endometriosis, a complex gynecological disorder, has been increasingly linked to gut microbiota dysbiosis, suggesting its potential role in disease pathogenesis. Methods This systematic review and meta-analysis explore the association between gut microbiota and endometriosis by evaluating alpha and beta diversity measures across 11 studies involving 1,727 women, including 433 diagnosed with endometriosis and 1,294 controls. Statistical analysis was performed utilizing either random effects models or fixed models by Revmen5.2 and STATA softwares. Results Significant differences in alpha diversity between endometriosis and control groups were observed using the Shannon Index (SMD = 0.39; p < 0.00001), Subgroup analysis showed significant differences for Chinese (SMD = 0.48; 95% CI = 0.14 to 0.82; p = 0.006; I 2 = 30%), Swedish, (SMD = 0.55; 95% CI = 0.27 to 0.83; p = 0.0001; I 2 = 30%) and Spanish (SMD = 0.34; 95% CI = −0.02 to 0.85; p < 0.06; I 2 = 27%), compared to others which highlighting the correlation between gut microbiota diversity and endometriosis across different demographic groups. The Simpson Index also revealed a notable difference in richness (SMD = 0.91; p = 0.03). However, no significant differences were detected using the Chao Index (SMD = 0.37; p = 0.11). These findings underscore the importance of diversity measures in understanding gut microbiota’s role in endometriosis. Seven studies employed PCoA, two used the Bray–Curtis dissimilarity index, and one performed PCA, revealing notable dissimilarities in gut microbiota composition between the groups. Using the Newcastle-Ottawa Scale, most studies scored ≥7 stars, indicating high quality. The funnel plot and Egger’s linear regression analysis indicated no publication bias. Conclusion This study highlights significant alterations in gut microbiota diversity and composition in women with endometriosis, emphasizing the potential role of gut microbiota in its pathogenesis. Future research should focus on standardizing reporting methods to facilitate deeper quantitative analyses. Systematic Review Registration PROSPERO (registration number RD42024611701).
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".