Cervicovaginal HIV-1 and herpes simplex virus type 2 shedding during genital ulcer disease episodes
Bibliographic record
Abstract
OBJECTIVE: To investigate correlates of herpes simplex virus type 2 (HSV-2) DNA and HIV-1 RNA among women with genital ulcer disease (GUD). DESIGN: Baseline data from a randomized placebo-controlled trial of episodic herpes treatment in Ghana and the Central African Republic. METHODS: GUD aetiology was determined by polymerase chain reaction (PCR) from a lesional swab. Real-time PCR was used to quantify HIV-1 RNA, and HSV-2 DNA in cervicovaginal lavages (CVL) and HIV-1 RNA in plasma. Genital infection was defined as the presence of virus in the lesion or CVL. RESULTS: Of 441 women enrolled, 79.0% were HSV-2 seropositive, 46.6% were HIV-1 seropositive, and 50.0% had an HSV-2 ulcer. Among 180 HSV-2/HIV-1 co-infected women, cervicovaginal HIV-1 RNA was detected more frequently in women with HSV-2 ulcers (67.9%) or cervicovaginal HSV-2 DNA only (72.3%) compared with women without genital HSV-2 infection (42.4%) (P = 0.004). Women with genital HSV-2 infection had higher median cervicovaginal HIV-1-RNA loads (3.14 log10 copies/mL versus 2.10 log10 copies/mL; P = 0.003), higher plasma HIV-1-RNA loads (median 5.10 versus 4.65 log10 copies/mL; P = 0.07), and lower median CD4 cell counts) (198 versus 409 cells/mm, P = 0.03). Cervicovaginal HIV-1 RNA and HSV-2 DNA were significantly correlated after adjusting for plasma HIV-1 RNA and CD4 cell counts (P < 0.001) and a 10-fold increase in cervicovaginal HSV-2 DNA was associated with a 1.7-fold increase in plasma HIV-1 RNA (P = 0.003). CONCLUSION: Genital HSV-2 infection is associated with increased cervicovaginal and plasma HIV-1 RNA among co-infected women with genital ulcers, independently of the level of immunodeficiency, highlighting the close interaction between these two viruses and the role of HSV-2 as a co-factor for the sexual transmission of HIV-1.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.004 | 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 teacher head, 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".