Prevalent Herpes Simplex Virus Type 2 Infection is Associated with Altered Vaginal Flora and an increased Susceptibility to Multiple Sexually Transmitted Infections
Bibliographic record
Abstract
BACKGROUND: Prevalent herpes simplex virus type 2 (HSV-2) infection increases human immunodeficiency virus acquisition. We hypothesized that HSV-2 infection might also predispose individuals to acquire other common sexually transmitted infections (STIs). METHODS: We studied the association between prevalent HSV-2 infection and STI incidence in a prospective, randomized trial of periodic STI therapy among Kenyan female sex workers. Participants were screened monthly for infection with Neisseria gonorrhoeae and Chlamydia trachomatis, and at least every 6 months for bacterial vaginosis (BV) and infection with Treponema pallidum, Trichomonas vaginalis, and/or HSV-2. RESULTS: Increased prevalence of HSV-2 infection and increased prevalence of BV were each associated with the other; the direction of causality could not be determined. After stratifying for sexual risk-taking, BV status, and antibiotic use, prevalent HSV-2 infection remained associated with an increased incidence of infection with N. gonorrhoeae (incidence rate ratio [IRR], 4.3 [95% confidence interval {CI}, 1.5-12.2]), T. vaginalis (IRR, 2.3 [95% CI, 1.3-4.2]), and syphilis (IRR, 4.7 [95% CI, 1.1-19.9]). BV was associated with increased rates of infection with C. trachomatis (IRR, 2.1 [95% CI, 1.1-3.8]) and T. vaginalis (IRR, 8.0 [95% CI, 3.2-19.8]). CONCLUSION; Increased prevalences of HSV-2 infection and BV were associated with each other and also associated with enhanced susceptibility to an overlapping spectrum of other STIs. Demonstration of causality will require clinical trials that suppress HSV-2 infection, BV, or both.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".