Infection with antiretroviral-susceptible HIV in an individual adherent to pre-exposure prophylaxis: strategies for treatment initiation
Bibliographic record
Abstract
HIV pre-exposure prophylaxis (PrEP) is effective at preventing sexual acquisition of HIV, and failures in clinical trials are largely attributable to medication nonadherence. We report here a case of infection with a fully susceptible strain of HIV in an individual adherent to PrEP as demonstrated by pharmacy records and intracellular tenofovir diphosphate levels. At diagnosis, the viral load was 90 copies/mL precluding initial genotype testing due to low copy number. While PrEP failure is rare, this case underscores the importance of regular HIV testing for patient on PrEP and prompts discussion regarding the approach to treatment following failure where an initial genotype is not yet available or not possible due to low viral load. Few other case reports of PrEP failure exist in the literature and approaches to treatment varied widely. We suggest the initial viral copy number may guide next steps and discuss the risks and benefits of stopping PrEP, escalating therapy with integrase inhibitors or boosted protease inhibitors, or switching to non-nucleoside antiretroviral treatment regimens.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".