Oestradiol concentrations in trans women with HIV suppressed on unboosted integrase inhibitor regimens versus trans women without HIV taking oral oestradiol: a pilot study
Bibliographic record
Abstract
BACKGROUND: Feminizing hormone therapy (FHT) is essential to many trans women. Concern about negative drug interactions between FHT and ART can be an ART adherence barrier among trans women with HIV. OBJECTIVES: In this single-centre, parallel group, cross-sectional pilot study, we measured serum oestradiol concentrations in trans women with HIV taking FHT and unboosted integrase strand transfer inhibitor (INSTI)-based ART versus trans women without HIV taking FHT. METHODS: We included trans women with and without HIV, aged ≥18 years, taking ≥2 mg/day of oral oestradiol for at least 3 months plus an anti-androgen. Trans women with HIV were on suppressive ART ≥3 months. Serum oestradiol concentrations were measured prior to medication dosing and 2, 4, 6 and 8 h post-dose. Median oestradiol concentrations were compared between groups using Wilcoxon rank-sum tests. RESULTS: Participants (n = 8 with HIV, n = 7 without) had a median age of 32 (IQR: 28, 39) years. Among participants, the median oral oestradiol dose was 4 mg (range 2-6 mg). Participants had been taking FHT for a median of 4 years (IQR: 2, 8). Six trans women with HIV were taking bictegravir/emtricitabine/tenofovir alafenamide and two were taking dolutegravir/abacavir/lamivudine. All oestradiol concentrations were not significantly different between groups. Eleven (73%) participants had target oestradiol concentrations in the range 200-735 pmol/L at C4h (75% among women with HIV, 71% among those without HIV). CONCLUSIONS: Oestradiol concentrations were not statistically different in trans women with HIV compared with those without HIV, suggesting a low probability of clinically relevant drug-drug interactions between FHT and unboosted INSTI-based ART.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".