Composition and Stability of the Vaginal Microbiota of Pregnant Women With Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD) is common in women of childbearing years, and active IBD during pregnancy is associated with increased rates of preterm delivery and low-birth-weight newborns. Changes in the vaginal microbiome have been associated with preterm delivery. We aimed to determine the taxonomic composition of the vaginal microbiota at 3 time points during pregnancy in a population of women with IBD. METHODS: Participants were recruited from the patient registry of the Preconception and Pregnancy IBD Clinic at Royal University Hospital in Saskatoon, Canada. Self-collected vaginal swabs were obtained from patients at each trimester. Microbiota profiles were created by cpn60 amplicon sequencing. RESULTS: We characterized the vaginal microbiota of 32 pregnant participants with IBD (33 pregnancies) during each trimester. A total of 32 of 33 pregnancies resulted in a live birth with 43.8% (n = 14 of 32, 2 missing) by caesarean section; 2 of 32 were preterm. Microbiota compositions corresponded to previously described community state types, with most participants having microbiota dominated by Lactobacillus crispatus. In 25 of 29 participants in which samples were available for more than 1 time point, there was no change in the community state type over time. Prevalence of Mollicutes (Mycoplasma and/or Ureaplasma) was significantly higher in pregnant participants with IBD than in a previously profiled cohort of 172 pregnant women without IBD who delivered at term. CONCLUSIONS: The vaginal microbiome of participants with IBD was stable throughout pregnancy. Prevalence of Mollicutes, which has been associated with preterm delivery, warrants further study in this patient group.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".