HIV pre‐exposure prophylaxis for people who inject drugs: a review of current results and an agenda for future research
Bibliographic record
Abstract
INTRODUCTION: Studies examining the use of pre-exposure prophylaxis (PrEP) to prevent HIV transmission among people who inject drugs (PWIDs) have not been adequately summarized. Recently, the Bangkok Tenofovir Study has shown that PrEP may be effective at reducing new HIV infections among this high-risk group. This randomized controlled trial was the first study to specifically examine the efficacy of PrEP among PWIDs. In this review, we present the current state of evidence regarding the use of PrEP to prevent HIV infection in PWID populations, and set an agenda for future research to inform the most effective implementation of PrEP in the context of existing evidence-based HIV prevention strategies. DISCUSSION: Despite positive trial results confirming that PrEP may prevent HIV transmission among PWIDs, there remain many questions regarding the interpretation of these results, as well as obstacles to the implementation of PrEP regimens within highly diverse drug-using communities. Aside from the Bangkok Tenofovir Study, we identified only one other published study that has collected empirical data to inform the use of PrEP among PWIDs. The large gap in research regarding the use and implementation of PrEP for PWIDs signals the need for further research and attention. CONCLUSIONS: We recommend that future research efforts focus on elucidating the generalizability of the Bangkok Tenofovir Study results in other injection drug-using populations, examining the willingness of PWIDs to use PrEP in diverse contexts, identifying barriers to adherence to PrEP regimens and determining the most effective ways to implement PrEP programmes within the context of existing evidence-based prevention strategies, including opioid substitution therapy and needle and syringe distribution programmes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".