The Role of Dermatovenereology in the Diagnosis and Management of Bacterial Vaginosis: A Systematic Review
Bibliographic record
Abstract
Background: Bacterial vaginosis (BV) is a prevalent, recurrent cause of abnormal vaginal discharge with important sexual and reproductive health implications. Because symptoms overlap with candidiasis, trichomoniasis, cervicitis/STIs, and vulvar dermatoses, dermatovenereology services are central to accurate diagnosis and comprehensive care. Methods: A PRISMA-compliant systematic review searched PubMed, EMBASE, and Scopus from inception to September 1, 2023, using controlled vocabulary and keywords related to BV, diagnostic modalities (Amsel, Nugent/Gram stain, microscopy, molecular assays), and dermatovenereology/sexual health services. Screening, full-text eligibility, and narrative synthesis were performed; risk of bias was assessed using the Newcastle–Ottawa Scale. Result: From 729 records, 8 studies were included after deduplication, screening, and eligibility assessment. Studies consistently highlighted the value of objective diagnosis particularly in recurrent, atypical, or post-treatment presentations. NAAT-based testing was used mainly in referral settings and facilitated concurrent STI testing. First-line antibiotics (metronidazole or clindamycin) achieved short-term response, but recurrence was common; suppressive intravaginal metronidazole and newer recurrence-prevention approaches (e.g., astodrimer gel, Lactin-V) reduced relapse in selected populations. Conclusions: Dermatovenereology-led pathways that integrate objective testing, careful differential diagnosis, STI screening, and counseling can improve diagnostic precision and reduce BV recurrence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".