P1-S2.62 Factors associated with high-risk penetrative sex in a cohort of treatment experienced HIV-positive men who have sex with men (MSM) in British Columbia
Bibliographic record
Abstract
Background In Canada, men who have sex with men (MSM) are disproportionately infected with HIV. Despite much evidence demonstrating the secondary preventive value of HAART, we have not fully capitalised on potential synergies between treatment and prevention. This study investigates high-risk sexual behaviour among treatment-experienced MSM in British Columbia, Canada. Methods We analysed data from the Longitudinal Investigations into Supportive and Ancillary Health Services (LISA) project on MSM (gay, bisexual, or reported sex with men in the 6 months prior to interview). High-risk sexual behaviour was penetrative anal or vaginal sex in the 6 months prior to interview with less than 100% condom use. Multivariate logistic regression was used to identify factors associated with high-risk penetrative sex. Results Of 346 HIV-positive MSM, median age was 46 years, 268 (78%) were currently on HAART, with 185 (54%) having ≥350 CD4 cells/μl. Ninety-eight (28%) participants endorsed seeking out HIV-positive partners for sex, and 147 (43%) reported being less likely to use a condom with an HIV-positive partner. In the regression model, HIV-positive MSM with a CD4 count ≥350 cells/μl were more likely to report unprotected penetrative sex (Adjusted OR [AOR] =2.7; 95% CI 1.5 to 5.2), more likely to not use condoms with their HIV-positive partners (AOR=12.0; 95% CI:6.4 to 22.3), and less likely to report sex with anonymous partners in the past 6 months (AOR=0.28; 95% CI 0.1 to 0.8). No significant associations were found between high-risk penetrative sex and current HAART use, viral suppression, or treatment adherence. Conclusion HIV-positive MSM who report engaging in high-risk penetrative sex are more likely to be healthier (higher CD4 counts), to have unprotected sex with other HIV-positive partners (serosorting) and with known rather than anonymous sex partners. Despite healthier MSM reporting more high-risk sex, results suggest this risk-taking is discriminate and would not necessarily lead to more onward HIV transmission.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.006 | 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".