P3.152 Prevalence of bacterial vaginosis infection and associated factors in women who have sex with women
Bibliographic record
Abstract
Introduction The present research aims to fill a gap in the national and international literature concerning prevalences and factors related to Bacterial vaginosis (VB) in Women who Have Sex with Women (WSW). Methods It is a cross sectional, analytical and non-radomized study with 128 WSW from Botucatu - SP and surrounding regions who answered the call from social media, mass communication means, health services and friends or acquaintances from January to November,2015. Data was obtained by the researchers involved in the main study, through interviews ang gynaecological exam. The diagnostic of VB was abteined through gram staining. Associations were estimated by multiple regression. Results The prevalence of BV was 41,1%% and factors associated were vaginal douching [OR=3,29 (IC:95%: 1,26–8,59) p=0014] and sex toys use[OR=2,34 (IC:95%: 1,00–5,50); p=0049]. Conclusion Considered as whole, these data lead to conclusion that the individuals of this study presented high vulnerability to STI/AIDS, as shown by the high prevalence of VB. This study clearly shows the need for a specific health assistance to these women, promoting prevention and education in a holistic approach.
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 | 0.000 | 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) | 0.010 | 0.001 |
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".