Baseline Factors Associated With Incident HIV and STI in Four Microbicide Trials
Bibliographic record
Abstract
BACKGROUND: Analyzing pooled data from 4 recent microbicide trials, we aimed to determine characteristics of participants at higher risk of HIV and sexually transmitted infections (STIs), to inform targeted recruitment, preserved study power, and potentially smaller study sizes in future trials. METHODS: We evaluated the relationships between participants' characteristics and the incidence of HIV, STIs, and reproductive tract infections (RTIs). We calculated incidence rates as the number of infection events divided by the person-years of observation. We applied Cox regression models to assess the relationships between baseline demographic, reproductive and behavioral factors and incident HIV, STIs and RTIs. RESULTS: The pooled incidence rates for HIV, chlamydia, and gonorrhea were 2.1, 6.4 and 9.9 per 100 person-years, respectively. Proportions of participants with trichomoniasis, bacterial vaginosis (BV), and candidiasis were 0.06, 0.40, and 0.40, respectively. In final multivariable models, age and education were significantly (and inversely) associated with incident HIV; baseline chlamydia, baseline trichomoniasis, and younger age were associated with incident Chlamydia; and baseline gonorrhea infection, younger age, less education, nulliparous status, baseline chlamydia, and condom use for contraception were associated with incident gonorrhea. Three factors were associated with trichomoniasis: baseline trichomoniasis infection, baseline chlamydia, and baseline BV. CONCLUSIONS: Only younger age was robustly associated with multiple STI outcomes in our multivariable analyses. Although there was little evidence of associations between baseline STIs and incident HIV, they were strongly associated with incident STIs. We found no evidence that measured baseline sexual behavior factors were associated with incident HIV or STIs.
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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 | 0.057 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.009 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".