Impact of maternal HIV-1 viremia on lymphocyte subsets among HIV-exposed uninfected infants: protective mechanism or immunodeficiency
Bibliographic record
Abstract
BACKGROUND: Reports of increased morbidity and mortality from infectious diseases among HIV Exposed Uninfected (HEU) infants have raised concern about a possible underlying immunodeficiency among them. The objective of this study was to assess the immunological profile of HEU infants born to mothers exhibiting different levels of HIV-1 viremia at the time of delivery. METHODS: Study subjects were enrolled in the Centre maternel et infantile sur le SIDA (CMIS) mother-child cohort between 1997 and 2010 (n =585). Infant CD4+ T cell, CD8+ T cell and CD19+ B cell counts were assessed at 2 and 6 months of age, and compared among HEU infants in groups defined by maternal viral load (VL) at the time of delivery (VL < 50 copies/ml, VL 50-1000 copies/ml, and VL > 1000 copies/ml) in a multivariable analysis. RESULTS: At 2 months of age, infants born to mothers with VL > 1000 copies/ml had lower CD4+ T cell counts compared to those born to mothers with VL < 50 copies/ml at the time of delivery (44.3% versus 48.3%, p = 0.007, and 2884 vs. 2432 cells/mm3, p = 0.02). These differences remained significant after adjusting for maternal and infant antiretroviral drug use, gender, race and gestational age, and persisted at 6 months of age. There were no differences in CD8+ T cell count or absolute CD19+ B cell count between groups, though higher CD19+ B cell percentage was seen among infants born to mothers with VL > 1000 copies/ml. CONCLUSIONS: These results suggest that exposure to high levels of HIV-1 viremia in utero, even in the absence of perinatal transmission, may affect the infant's developing immune system. While further work needs to be done to confirm these findings, they reinforce the need for optimal treatment of HIV infected pregnant women, and careful follow-up of HEU infants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".