HIV Protease Inhibitor Use During Pregnancy Is Associated With Decreased Progesterone Levels, Suggesting a Potential Mechanism Contributing to Fetal Growth Restriction
Bibliographic record
Abstract
BACKGROUND: Protease inhibitor (PI)-based combination antiretroviral therapy (cART) is administered during pregnancy to prevent perinatal human immunodeficiency virus (HIV) transmission. However, PI use has been associated with adverse birth outcomes, including preterm delivery and small-for-gestational-age (SGA) births. The mechanisms underlying these outcomes are unknown. We hypothesized that PIs contribute to these adverse events by altering progesterone levels. METHODS: PI effects on trophoblast progesterone production were assessed in vitro. A mouse pregnancy model was used to assess the impact of PI-based cART on pregnancy outcomes and progesterone levels in vivo. Progesterone levels were assessed in plasma specimens from 27 HIV-infected and 17 HIV-uninfected pregnant women. RESULTS: PIs (ritonavir, lopinavir, and atazanavir) but not nucleoside reverse transcriptase inhibitors (NRTIs) or nonnucleoside reverse transcriptase inhibitors reduced trophoblast progesterone production in vitro. In pregnant mice, PI-based cART but not dual-NRTI therapy was associated with significantly lower progesterone levels that directly correlated with fetal weight. Progesterone supplementation resulted in a significant improvement in fetal weight. We observed lower progesterone levels and smaller infants in HIV-infected women receiving PI-based cART, compared with the control group. In HIV-infected women, progesterone levels correlated significantly with birth weight percentile. CONCLUSIONS: Our data suggest that PI use in pregnancy may lead to lower progesterone levels that could contribute to adverse birth outcomes.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".