Serosorting and HIV/STI Infection among HIV-Negative MSM and Transgender People: A Systematic Review and Meta-Analysis to Inform WHO Guidelines
Bibliographic record
Abstract
We conducted a systematic review and meta-analysis to assess the association between serosorting and HIV infection, sexually transmitted infections (STIs), and quality of life among men who have sex with men (MSM) and transgender people. Two reviewers independently screened abstracts and abstracted data. Meta-analyses were conducted using random effects models. Of 310 citations reviewed, 4 observational studies, all with MSM, met inclusion criteria. Compared to consistent condom use, serosorting was associated with increased risk of HIV (3 studies, odds ratio (OR): 1.80, 95% confidence interval (CI):1.21-2.70) and bacterial STIs (1 study, OR: 1.62, 95% CI: 1.44-1.83). Compared to no condom use, serosorting was associated with reduced risk of HIV (3 studies, OR: 0.46, 95% CI: 0.25-0.83) and bacterial STIs (1 study, OR: 0.81, 95% CI: 0.73-0.91). Among HIV-negative MSM, condom use appears to be more protective against HIV and STIs than serosorting and should be encouraged. However, serosorting may be better than no condom use as a harm reduction strategy.
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 | 0.018 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.025 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".