Post‐exposure prophylaxis following consented sexual exposure: impact of national recommendations on user profile, drug regimens and estimates of averted HIV infections
Bibliographic record
Abstract
OBJECTIVES: The aim of the study was to describe the characteristics, impact and outreach of post-exposure prophylaxis (PEP) for sexual exposure in Brazil. METHODS: We used secondary data from the Brazilian Ministry of Health to describe the impact of national guidelines on the frequency of prescription, user profile and antiretroviral regimens. We also estimated the number of potentially averted HIV infections attributable to PEP for consented sexual exposure between 2009 and 2017. RESULTS: A total of 260 457 PEP regimens were prescribed to individuals ≥ 14 years old; 104 613 (40.2%) were prescribed for consented sexual exposure, with an increasing frequency since 2011. Drugs used in PEP regimens underwent significant modifications during the period, reflecting national recommendations. We estimated that there were up to 3138 potentially averted HIV infections attributable to PEP for consented sexual exposure between 2009 and 2017. CONCLUSIONS: In the context of a combined HIV prevention strategy, PEP is still an essential tool for individuals for whom other methods are contraindicated or fail to be applied.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".