Circulating levels of inflammatory mediators in pregnant people living with HIV according to antiretroviral therapy regimen
Bibliographic record
Abstract
Introduction: The use of antiretroviral therapy (ART) during pregnancy, particularly protease-inhibitor-based regimens (PI), has been linked to adverse outcomes including preterm delivery. As this outcome may be related to systemic inflammation, we sought to characterize inflammatory profiles of pregnant people living with HIV (PLWH) by comparing their levels of inflammatory mediators at two timepoints during pregnancy according to ART regimen, and to HIV-negative controls. Methods: Second and third trimester samples from 144 pregnant PLWH treated with ART and 24 HIV-uninfected controls were retrieved from the CARMA-PREG cohort. Peripheral plasma levels of 12 inflammatory mediators previously linked to HIV infection and/or poor pregnancy outcomes were quantified by multiplex assay: HMGB1, GM-CSF, IFNα, IFNβ, IFNγ, IL-10, IL-17, IL-1β, IL-6, TNFα, AGP, and CRP. Levels were compared by ART regimen and HIV status. Results: Adjusted analyses showed that PLWH have higher levels of AGP throughout pregnancy and lower levels of IFNγ and IL-1β during the second trimester. PI-based regimens are associated with significantly higher levels of IFNα and IL-17 during the second trimester and IFNα, CRP, HMGB1, and IFNβ during the third trimester compared to InSTI-based regimens. The PI-subgroup was associated with preterm delivery and higher HIV-1 viral load. Discussion: Our results suggest that PI-based regimens are associated with a pro-inflammatory and antiviral immunological response and a high viral load, which may be a mechanism through which PI-based regimens increase the risk of preterm delivery. Further investigations into cellular mechanisms and pro-inflammatory cascades leading to preterm delivery are necessary to support this association.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".