Doxycycline Prophylaxis for Bacterial Sexually Transmitted Infections
Bibliographic record
Abstract
Bacterial sexually transmitted infections (STIs) have been increasing over the past 2 decades in gay, bisexual, and other men who have sex with men. With the widespread use of early human immunodeficiency virus (HIV) treatment, which virtually eliminates transmission risk, and the availability of HIV pre-exposure prophylaxis, there have been attitudinal changes regarding HIV infection with resultant increases in sexual contact and declines in condom use. Doxycycline is used for primary prophylaxis in a number of infectious diseases. We conducted a state-of-the-art review to examine the current state of research, knowledge gaps, and challenges around the use of doxycycline prophylaxis to prevent syphilis and other STIs. International academic and government experts met in March 2019 to frame the initial inquiry, which was supplemented by focused literature searches. Two small short-term randomized controlled trials examining doxycycline prophylaxis found high efficacy. Five additional clinical studies are underway or in development. Studies differed in design, population, outcomes, and safety measures. Doxycycline prophylaxis for bacterial STIs shows promise. Better and more robust data are needed on efficacy; target population; community acceptability; behavioral risk compensation; doxycycline dose, regimen, and formulation; long-term safety; antimicrobial resistance; cost-effectiveness; and risk-benefit.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".