Episodic Therapy for Genital Herpes in Sub-Saharan Africa: A Pooled Analysis from Three Randomized Controlled Trials
Bibliographic record
Abstract
A randomized controlled trial in South Africa found a beneficial effect of acyclovir on genital ulcer healing, but no effect was seen in trials in Ghana, Central African Republic and Malawi. The aim of this paper is to assess whether the variation in impact of acyclovir on ulcer healing in these trials can be explained by differences in the characteristics of the study populations.Pooled data were analysed to estimate the impact of acyclovir on the proportion of ulcers healed seven days after randomisation by HIV/CD4 status, ulcer aetiology, size and duration before presentation; and impact on lesional HIV-1. Risk ratios (RR) were estimated using Poisson regression with robust standard errors. Of 1478 patients with genital ulcer, most (63%) had herpetic ulcers (16% first episode HSV-2 ulcers), and a further 3% chancroid, 2% syphilis, 0.7% lymphogranuloma venereum and 31% undetermined aetiology. Over half (58%) of patients were HIV-1 seropositive. The median duration of symptoms before presentation was 6 days. Patients on acyclovir were more likely to have a healed ulcer on day 7 (63% vs 57%, RR = 1.08, 95% CI 0.98-1.18), shorter time to healing (p = 0.04) and less lesional HIV-1 RNA (p = 0.03). Small ulcers (<50 mm(2)), HSV-2 ulcers, first episode HSV-2 ulcers, and ulcers in HIV-1 seropositive individuals responded best but the better effectiveness in South Africa was not explained by differences in these factors.There may be slight benefit in adding acyclovir to syndromic management in settings where most ulcers are genital herpes. The stronger effect among HIV-1 infected individuals suggests that acyclovir may be beneficial for GUD/HIV-1 co-infected patients. The high prevalence in this population highlights that genital ulceration in patients with unknown HIV status provides a potential entry point for provider-initiated HIV testing.
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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 | 0.021 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.024 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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 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".