Pre-exposure prophylaxis and bacterial sexually transmitted infections (STIs) among gay and bisexual men
Bibliographic record
Abstract
OBJECTIVES: While pre-exposure prophylaxis (PrEP) prevents HIV acquisition among gay, bisexual and other men who have sex with men (GBM), PrEP-using GBM may be more likely to engage in sexual behaviours associated with bacterial STIs. We examined associations between PrEP use, condomless anal sex (CAS), number of anal sex partners, oral sex and bacterial STI diagnoses among GBM living in Canada's three largest cities. METHODS: Among HIV-negative/unknown-status GBM in the baseline of the Engage cohort study, we fit a structural equation model of the associations between any PrEP use, sexual behaviours and bacterial STI diagnosis. We estimated direct and indirect paths between PrEP use and STI via CAS, number of anal sex partners and oral sex. RESULTS: The sample included 2007 HIV-negative/unknown status GBM in Montreal, Toronto and Vancouver. There was a significant direct association between PrEP use and current STI diagnosis (β=0.181; 95% CI: 0.112 to 0.247; p<0.001), CAS (β=0.275; 95% CI: 0.189 to 0.361; p<0.001) and number of anal sex partners (β=0.193; 95% CI: 0.161 to 0.225; p<0.001). In the mediated model, the direct association between PrEP use and STIs was non-significant. However, the indirect paths from PrEP to CAS to STIs (β=0.064; 95% CI: 0.025 to 0.120; p=0.008), and from PrEP to greater number of anal sex partners to CAS to STIs were significant (β=0.059; 95% CI: 0.024 to 0.108; p=0.007). CONCLUSIONS: Our study adds to the growing awareness that PrEP use among GBM may be associated with bacterial STIs because PrEP users have more anal sex partners and are more likely to engage in CAS. The results underscore the importance of providing effective STI counselling and regular testing to PrEP users, adapting PrEP care and related STI testing to individual needs, and the need for effective prevention strategies for bacterial 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".