STI prevalence among men living with HIV engaged in safer conception care in rural, southwestern Uganda
Bibliographic record
Abstract
HIV care provides an opportunity to integrate comprehensive sexual and reproductive healthcare, including sexually transmitted infection (STI) management. We describe STI prevalence and correlates among men living with HIV (MLWH) accessing safer conception care to conceive a child with an HIV-uninfected partner while minimizing HIV transmission risks. This study reflects an ongoing safer conception program embedded within a regional referral hospital HIV clinic in southwestern Uganda. We enrolled MLWH, planning for pregnancy with an HIV-uninfected partner and accessing safer conception care. Participants completed interviewer-administered questionnaires detailing socio-demographics, gender dynamics, and sexual history. Participants also completed STI laboratory screening for syphilis (immunochromatographic testing confirmed by rapid plasma reagin), and chlamydia, gonorrhea, trichomoniasis, and HIV-RNA via GeneXpert nucleic acid amplification testing. Bivariable associations of STI covariates were assessed using Fisher's exact test. Among the 50 men who completed STI screening, median age was 33 (IQR 31-37) years, 13/50 (26%) had ≥2 sexual partners in the prior three months, and 46/50 (92%) had HIV-RNA <400 copies/mL. Overall, 11/50 (22%) had STIs: 16% active syphilis, 6% chlamydia. All participants initiated STI treatment. STI prevalence was associated with the use of threats/intimidation to coerce partners into sex (27% vs 3%; p = 0.03), although absolute numbers were small. We describe a 22% curable STI prevalence among a priority population at higher risk for transmission to partners and neonates. STI screening and treatment as a part of comprehensive sexual and reproductive healthcare should be integrated into HIV care to maximize the health of men, women, and children.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".