Different and diverse anaerobic microbiota were seen in women living with <scp>HIV</scp> with unsuppressed <scp>HIV</scp> viral load and in women with recurrent bacterial vaginosis: a cohort study
Bibliographic record
Abstract
OBJECTIVE: To compare the vaginal microbiota of women living with HIV (WLWH) with the vaginal microbiota of women with recurrent bacterial vaginosis (BV) and healthy women without HIV to determine if there are differences in the vaginal microbiome, what factors influence these differences, and to characterise HIV clinical parameters including viral load and CD4 count in relation to the vaginal microbiome. DESIGN: Observational cohort study. SETTING: Canada. POPULATION: Women aged 18-49 years who were premenopausal and not pregnant were recruited into three cohorts: healthy women, WLWH and women with recurrent BV. METHODS: Demographic and clinical data were collected via interviews and medical chart reviews. Vaginal swabs were collected for Gram-stain assessment and microbiome profiling using the cpn60 barcode sequence. MAIN OUTCOME MEASURES: To compare overall community composition differences, we used compositional data analysis methods, hierarchical clustering and Kruskal-Wallis tests where appropriate. RESULTS: Clinical markers such as odour and abnormal discharge, but not irritation, were associated with higher microbial diversity. WLWH with unsuppressed HIV viral loads were more likely than other groups to have non-Gardnerella-dominated microbiomes. HIV was associated with higher vaginal microbial diversity and this was related to HIV viral load, with unsuppressed women demonstrating significantly higher relative abundance of Megasphaera genomosp. 1, Atopobium vaginae and Clostridiales sp. (all P < 0.05) compared with all other groups. CONCLUSIONS: In WLWH, unsuppressed HIV viral loads were associated with a distinct dysbiotic profile consisting of very low levels of Lactobacillus and high levels of anaerobes. TWEETABLE ABSTRACT: Vaginal microbiomes in WLWH with viral load >50 copies/ml have distinct dysbiotic profiles with high levels of anaerobes.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".