CHRONIC PELVIC PAIN SYNDROME IN WOMEN WITH VAGINAL DYSBIOSIS: A SYSTEMATIC REVIEW OF PRESENTATION, DIAGNOSIS, AND MANAGEMENT
Bibliographic record
Abstract
Background: Chronic pelvic pain syndrome (CPPS) with vaginal dysbiosis is challenging to diagnose and can significantly affect women's health and daily life. Objective: To review recent research on the symptoms, diagnosis, and treatment of CPPS with vaginal dysbiosis, and to summarize new findings and clinical practices. Methods: Articles from PubMed, Scopus, and Google Scholar published between 2000 and 2025 were included. The review focused on original studies and systematic reviews involving adult women with CPPS and vaginal microbiota assessment. Case reports, non-English articles, and studies lacking vaginal microbiota analysis were excluded from the analysis. Data extraction and quality assessment were conducted using the Newcastle-Ottawa Scale and AMSTAR 2. Results: Women with CPPS and vaginal dysbiosis often experience persistent pelvic pain, sexual and urinary symptoms, and emotional distress. Diagnosis typically includes clinical examination, laboratory testing, and vaginal microbiota analysis using bacterial or genetic methods. Treatment may involve antibiotics, microbiota restoration, physical therapy, and mental health support. Advances in vaginal microbiome research and precision medicine are expected to shape future treatments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".