Bacterial sexually transmitted infections are concentrated in subpopulations of men who have sex with men using HIV pre-exposure prophylaxis
Bibliographic record
Abstract
OBJECTIVE: Studies have shown varying trends in incidence of sexually transmitted infections (STIs) among individuals using HIV pre-exposure prophylaxis (PrEP). Characterization of individuals at increased risk for STIs may offer an opportunity for targeted STI screening. DESIGN: Group-based trajectory modeling. METHODS: We screened participants from the AMPrEP demonstration project (2015-2020) for urogenital, anal, and pharyngeal chlamydia and gonorrhea, and syphilis every 3 months and when needed. We identified trajectories of STI incidence within individuals over time and determinants of belonging to a trajectory group. We calculated cumulative proportions of STIs within STI trajectory groups. RESULTS: Three hundred and sixty-six participants with baseline and at least one screening visit during follow-up were included (median follow-up time = 3.7 years [interquartile range, IQR = 3.5-3.7]). We identified three trajectories of STI incidence: participants with a mean of approximately 0.1 STIs per 3 months ('low overall', 52% of the population), participants with a mean 0.4 STI per 3 months ('medium overall', 43%), and participants with high and fluctuating (between 0.3 and 1 STIs per 3 months) STI incidence ('high and fluctuating', 5%). Participants in the 'low overall' trajectory were significantly older, and reported less chemsex and condomless anal sex with casual partners than participants in the other trajectories. Participants in the 'high and fluctuating' and 'medium overall' groups accounted for respectively 23 and 64% of all STIs observed during follow-up. CONCLUSIONS: STI incidence was concentrated in subpopulations of PrEP users who were younger, had more chemsex and condomless anal sex. Screening frequency for STIs could be reduced for subpopulations with low risk for incident STIs.
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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 | 0.001 |
| 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) | 0.000 | 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".