Mother‐to‐Child Transmission of GB Virus C in a Cohort of Women Coinfected with GB Virus C and HIV in Bangkok, Thailand
Bibliographic record
Abstract
BACKGROUND: GB virus C (GBV-C) is an apathogenic virus that inhibits human immunodeficiency virus (HIV) replication in vitro. Mother-to-child transmission (MTCT) of GBV-C has been observed in multiple small studies. Our study examined the rate and correlates of MTCT of GBV-C in a large cohort of GBV-C-HIV-coinfected pregnant women in Thailand. METHODS: Maternal delivery plasma specimens from 245 GBV-C-HIV-infected women and specimens from their infants at 4 or 6 months of age were tested for GBV-C RNA. Associations with MTCT of GBV-C were examined using logistic regression. RESULTS: One hundred one (41%) of 245 infants acquired GBV-C infection. MTCT of GBV-C was independently associated with maternal antiretroviral therapy (adjusted odds ratio [AOR], 5.21 [95% confidence interval {CI}, 2.12-12.81]), infant HIV infection (AOR, 0.05 [95% CI, 0.01-0.26]), maternal GBV-C load (8.0 log(10) copies/mL: AOR, 86.77 [95% CI, 15.27-481.70]; 7.0-7.9 log(10) copies/mL: AOR, 45.62 [95% CI, 8.41-247.51]; 5.0-6.9 log(10) copies/mL: AOR, 9.07 [95% CI, 1.85-44.33]: reference, <5 log(10) viral copies/mL), and caesarean delivery (AOR, 0.26 [95% CI, 0.12-0.59]). CONCLUSIONS: Associations with maternal GBV-C load and mode of delivery suggest transmission during pregnancy and delivery. Despite mode of delivery being a common risk factor for virus transmission, GBV-C and HIV were rarely cotransmitted. The mechanisms by which maternal receipt of antiretroviral therapy might increase MTCT of GBV-C 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".