The Impact of GB Virus C co-infection on Mother to Child transmission of Human Immunodeficiency Virus
Bibliographic record
Abstract
GB virus C (GBV-C) is a common, apathogenic virus that can inhibit human immunodeficiency virus (HIV) replication in vitro. Persistent coinfection with GBV-C\nhas been associated with improved survival among HIV-infected adults while loss of\nGBV-C viremia has been associated with poor survival. If GBV-C does inhibit HIV\nreplication, it is possible that GBV-C infection may reduce mother-to-child-transmission (MTCT) of HIV. This study investigated whether maternal or infant GBV-C infection was associated with reduced MTCT of HIV infection. The study population consisted of 1,783 pregnant women from three Bangkok perinatal HIV transmission studies (1992-94, 1996-7, 1999-2004). We tested plasma collected at delivery for GBV-C RNA, GBV-C antibody, and GBV-C viral genotype. If maternal GBV-C RNA was detected, the four- or six-month infant specimen was tested for GBV-C RNA. Rates of MTCT of HIV in GBV-C-infected and GBV-C-uninfected women and infants were compared using multiple logistic regression as were associations with MTCT of GBV-C and prevalence of GBV-C infection.\nThe prevalence of GBV-C infection (i.e. presence of RNA or antibody) was 33%\namong HIV-infected women and 15% among HIV-uninfected women. Forty-one percent\nof GBV-C-RNA-positive women transmitted GBV-C to their infants. Only two of 101\n(2.0%) GBV-C-RNA-positive infants acquired HIV infection compared to 162 (13.2%)\nof 1,232 of GBV-C-RNA-negative infants (RR 0.15, p<0.0001). This association\nremained after adjustment for maternal HIV viral load, antiretroviral prophylaxis, CD4+\ncount and other covariates. MTCT of HIV was not associated with presence of maternal\nGBV-C RNA or maternal GBV-C antibody. Maternal receipt of antiretroviral therapy\nwas associated with increased MTCT of GBV-C, as was high GBV-C viral load, vaginal\ndelivery and absence of infant HIV infection. GBV-C infection among women was\nindependently associated with more than one lifetime sexual partner, intravenous drug\nuse and HIV-infection.\nWe observed a higher prevalence of GBV-C infection among HIV-infected compared to HIV-uninfected pregnant women in Thailand, likely due to common risk factors. Antiretroviral therapy appears to increase MTCT of GBV-C. Infant GBV-C acquisition, but not maternal GBV-C infection, was significantly associated with reduced MTCT of HIV. Mechanisms for these later two associations are 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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".