Intermediate vaginal flora and bacterial vaginosis are associated with the same factors: findings from an exploratory analysis among female sex workers in Africa and India
Bibliographic record
Abstract
OBJECTIVES: Several recent studies suggest that intermediate vaginal flora (IVF) is associated with similar adverse health outcomes as bacterial vaginosis (BV). Yet, it is still unknown if IVF and BV share the same correlates. We conducted a cross-sectional and exploratory analysis of data from women screened prior to enrolment in a microbicide trial to estimate BV and IVF prevalence and examine their respective correlates. METHODS: Participants were interviewed, examined and provided blood and genital samples for the diagnosis of IVF and BV (using Nugent score) and other reproductive tract infections. Polytomous logistic regressions were used in estimating respective ORs of IVF and BV, in relation to each potential risk factor. RESULTS: Among 1367 women, BV and IVF prevalences were 47.6% (95% CI 45.0% to 50.3%) and 19.2% (95% CI 17.1% to 21.2%), respectively. Multivariate polytomous analysis of IVF and BV showed that they were generally associated with the same factors. The respective adjusted ORs were for HIV 1.98 (95% CI 1.37 to 2.86) and 1.62 (95% CI 1.20 to 2.20) (p=0.2248), for gonorrhoea 1.25 (95% CI 0.64 to 2.4) and 2.01 (95% CI 1.19 to 3.49) (p=0.0906), for trichomoniasis 3.26 (95% CI 1.71 to 6.31) and 2.39 (95% CI 1.37 to 4.33) (p=0.2630), for candidiasis 0.52 (95% CI 0.36 to 0.75) and 0.59 (95% CI 0.44 to 0.78) (p=0.5288), and for hormonal contraception 0.65 (95% CI 0.40 to 1.04) and 0.62 (95% CI 0.43 to 0.90) (p=0.8819). In addition, the association between vaginal flora abnormalities and factors such as younger age, HIV, gonorrhoea trichomoniasis and candidiasis were modified by the study site (all p for interaction ≤0.05). CONCLUSIONS: IVF has almost the same correlates as BV. The relationship between some factors and vaginal flora abnormalities may be site-specific.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".