Sexually Transmitted Infections in Pregnant People With Human Immunodeficiency Virus: Temporal Trends, Demographic Correlates, and Association With Preterm Birth
Bibliographic record
Abstract
BACKGROUND: We describe trends in prevalence and identify factors associated with Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), syphilis, and Trichomonas vaginalis (TV) diagnosed in pregnancy among US people with human immunodeficiency virus (PWH) and evaluate associations of sexually transmitted infections (STIs) with preterm birth (PTB). METHODS: We included pregnant PWH enrolled in the Surveillance Monitoring for ART Toxicities dynamic cohort of the Pediatric HIV/AIDS Cohort Study network who delivered between 2010 and 2019. Multivariable log-binomial or Poisson generalized estimating equation models were used to estimate the association of calendar year with each STI, controlling for confounders; the association of demographic and clinical factors with each STI; and the association of each STI with PTB. RESULTS: The sample included 2241 pregnancies among 1821 PWH. Median age at delivery was 29.2 years; 71% of participants identified as Black or African American. STI prevalence was: CT 7.7%, NG 2.3%, syphilis 2.4%, and TV 14.5%; 30% had unknown TV status. There were no temporal changes in STI prevalence. Younger age and initial HIV viral load ≥400 copies/mL were associated with increased risk of CT, NG, and TV. Recreational substance use was a risk factor for NG, syphilis, and TV. No STI was associated with PTB. CONCLUSIONS: Unlike nationwide trends, no changes in STI prevalence during the study period were observed. The large proportion with unknown TV status underscores the need for increased adherence to screening guidelines. STIs diagnosed during pregnancy in PWH were not associated with risk of PTB.
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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 | 0.003 |
| 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) | 0.001 | 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".