HIV Postexposure Prophylaxis and the Need for Drug Interaction Screening
Bibliographic record
Abstract
INTRODUCTION Certain antiretroviral medications are known to be involved in numerous drug interactions through their inhibition of the cytochrome P450 system.1,2 One of the uses of antiretroviral medications is postexposure prophylaxis (PEP) against HIV, to reduce the risk of infection among people who may have been exposed to the virus, either through occupational exposure (e.g., needlestick injuries) or non-occupational exposure (e.g., sexual assault).3,4 To maximize effectiveness in this situation, antiretroviral therapy must be started as soon as possible (preferably within hours of exposure)3-5; therefore, if a person is deemed a suitable candidate for prophylaxis, an HIV PEP “starter kit” is often given to the patient in the emergency department or other ambulatory setting to ensure prompt initiation. When providing HIV PEP in this setting, a systematic approach for identifying possible drug interactions may be lacking. As illustrated by the following case, these interactions can have severe consequences if not promptly identified and resolved.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".