Initiation of Antiretroviral Therapy Before Pregnancy Reduces the Risk of Infection-related Hospitalization in Human Immunodeficiency Virus–exposed Uninfected Infants Born in a High-income Country
Bibliographic record
Abstract
Background Epidemiological studies conducted in low- and high-income countries showed that infants exposed to maternal human immunodeficiency virus (HIV) have a high risk of severe infections. Immune alterations during fetal life have been proposed as a possible mechanism. Methods This prospective study assessed the relative risk of hospitalization for infection in HIV-exposed uninfected (HEU) infants as compared to HIV-unexposed (HU) infants born in a high-income country (HIC). Markers of monocyte activation and levels of pathogen-specific antibodies were measured at birth to identify correlates of infant susceptibility. Results There were 27 of 132 HEU infants and 14 of 123 HU infants hospitalized for infection during the first year of life (adjusted hazard ratio [aHR] 2.33, 95% confidence interval [CI] 1.10-4.97). Most of this increased risk was associated with the time of initiation of maternal antiretroviral therapy (ART). As compared to HU infants, the risk of hospitalization for infection of HEU infants was 4-fold higher when mothers initiated ART during pregnancy (aHR 3.84, 95% CI 1.69-8.71) and was not significantly increased when ART was initiated before pregnancy (aHR 1.42, 95% CI 0.58-3.48). The activation of newborn monocytes and the reduced transfer of maternal antibodies were most intense following ART initiation during pregnancy, and predicted the risk of infant hospitalization. Conclusions These observations indicate that initiation of maternal ART before pregnancy reduces the susceptibility of HEU infants born in a HIC to severe infections, and that this effect could be related to the prevention of immune alterations during fetal life.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| 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".