Reduced Mother‐to‐Child Transmission of HIV Associated with Infant but not Maternal GB Virus C Infection
Bibliographic record
Abstract
BACKGROUND: Prolonged coinfection with GB virus C (GBV-C) has been associated with improved survival in human immunodeficiency virus (HIV)-infected adults. We investigated whether maternal or infant GBV-C infection was associated with mother-to-child transmission (MTCT) of HIV-1 infection. METHODS: The study population included 1364 HIV-infected pregnant women enrolled in 3 studies of MTCT of HIV in Bangkok, Thailand (the studies were conducted from 1992-1994, 1996-1997, and 1999-2004, respectively). We tested plasma collected from pregnant women at delivery for GBV-C RNA, GBV-C antibody, and GBV-C viral genotype. If GBV-C RNA was detected in the maternal samples, the 4- or 6-month infant sample was tested for GBV-C RNA. The rates of MTCT of HIV among GBV-C-infected women and infants were compared with the rates among women and infants without GBV-C infection. RESULTS: The prevalence of GBV-C RNA in maternal samples was 19%. Of 245 women who were GBV-C RNA positive, 101 (41%) transmitted GBV-C to their infants. Of 101 infants who were GBV-C RNA positive, 2 (2%) were infected with HIV, compared with 162 (13%) of 1232 infants who were GBV-C RNA negative (odds ratio [OR] adjusted for study, 0.13 [95% confidence interval {CI}, 0.03-0.54]). This association remained after adjustment for maternal HIV viral load, receipt of antiretroviral prophylaxis, CD4(+) count, and other covariates. MTCT of HIV was not associated with the presence of GBV-C RNA (adjusted OR [aOR], 0.94 [95% CI, 0.62-1.42]) or GBV-C antibody (aOR, 0.90 [95% CI, 0.54-1.50]) in maternal samples. CONCLUSIONS: Reduced MTCT of HIV was significantly associated with infant acquisition of GBV-C but not with maternal GBV-C infection. The mechanism for this association remains unknown.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".