UK guideline for the use of HIV post‐exposure prophylaxis 2021
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We present the updated British Association for Sexual Health and HIV (BASHH) guidelines for post-exposure prophylaxis (PEP) to HIV following sexual exposures, occupational exposures and other nonoccupational exposures in the community. This serves as an update to the 2015 BASHH guideline on PEP following sexual exposures and the 2008 Expert Advisory Group on AIDS guidelines on HIV PEP. We aim to provide evidence-based guidance on best clinical practice in the provision, monitoring and support of PEP for the prevention of HIV acquisition following sexual, occupational and other nonoccupational exposures in the community. The guideline covers when to prescribe PEP, what antiretroviral agents to use and how to manage PEP. This includes (i) evidence of PEP efficacy; (ii) evidence relating to individual-level efficacy of antiretroviral therapy to prevent the sexual transmission of HIV; (iii) data on the detectable (transmissible) prevalence of HIV in specific populations; (iv) risk of HIV transmission following different types of sexual and occupational exposure; (v) baseline risk assessment; (vi) drug regimens and dosing schedules; (vii) monitoring PEP; (viii) baseline and follow-up blood-borne virus testing; (ix) the role of PEP within broader HIV prevention strategies, for example, HIV pre-exposure prophylaxis (PrEP). The guideline also covers special scenarios such as PEP in pregnancy, breastfeeding and chronic hepatitis B virus infection, and when PEP should be considered in people using HIV PrEP. The guidelines are aimed at clinical professionals directly involved in PEP provision and other stakeholders in the field. A proforma to assist PEP consultations is included. A public consultation process was undertaken prior to finalizing the recommendations.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 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 it