Evaluation of Gut Microbiota in Patients With Vulvovestibular Syndrome
Bibliographic record
Abstract
BACKGROUND: Vulvovestibular syndrome (VVS) or vulvodynia is a chronic, heterogeneous and multifactorial disease that dramatically affects women's health and quality of life. Despite important advancements in understanding VVS etiology have been achieved in the past decades, VVS still remains an elusive and complex condition without identifiable causes and effective treatments. In the present observational, retrospective, case-control study, we sought to investigate whether gut dysbiosis developed in patients with VVS. METHODS: To this aim, we compared both bacterial and fungal composition in VVS patients (n = 74; 34.3 ± 10.9 years old) with those of women without gynecological symptoms (n = 13 healthy control; 38.3 ± 10.4 years old). Furthermore, to assess whether gut ecology may have an impact on gut function, the degree of intestinal inflammation (calprotectin levels) and gut permeability (zonulin levels) were also evaluated. RESULTS: along with increased colonization of mold/yeast compared to healthy controls. Furthermore, fecal levels of zonulin indicated that in VVS patients gut dysbiosis translated into increased gut permeability. CONCLUSION: Our preliminary study, by demonstrating that alterations in gut microbiota and intestinal permeability are present in patients with VVS, highlights the novel notion that gut dysbiosis may be considered an important associated factor for VVS. These findings, if confirmed, may be clinically relevant and may help in choosing further diagnostic methods and more effective therapies for these patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".