Acquired syphilis in the context of pre-exposure prophylaxis for HIV: a systematic review of the scientific literature
Bibliographic record
Abstract
The aim of this study was systematically review the acquired syphilis before and during follow-up of pre-exposure prophylaxis (PrEP) for HIV. We analyzed articles that studied PrEP users with the outcome of acquired syphilis. The eligibility criteria were studies retrieved from the United States National Library of Medicine (Pubmed), Latin American and Caribbean Health Sciences Literature (Lilacs), Embase and Scopus databases, published between 2012 and 2023, in English, Spanish or Portuguese. We performed the descriptive synthesis and quality analysis of selected studies using the Newcastle Ottawa scale or Cochrane scale. We also used random-effects models to generate pooled rate estimates for syphilis before PrEP and during follow-up. A total of 4412 studies were found and 35 were selected, all in English, and almost all with high or satisfactory quality. The review found a PrEP syphilis rate of 6.0%. A summary of three studies estimated a 2.34-fold increased risk of syphilis acquisition during PrEP, with an incidence rate of 8.89 cases/100 person-years. These findings warrant caution due to study heterogeneity. Compared to HIV-positive individuals, PrEP users exhibit potentially higher syphilis rates, particularly among those aged 33-38 years, and factors such as age ≥ 35 years, MSM status, prior sexually-transmitted infections, and longer PrEP duration (every 6 months) are associated. Future research should further investigate these PrEP-related factors contributing to heightened syphilis risk.
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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 | 0.009 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".