Prevalence and correlates of GB virus C infection in HIV‐infected and HIV‐uninfected pregnant women in Bangkok, Thailand
Bibliographic record
Abstract
GB virus C (GBV-C) is an apathogenic virus that has been shown to inhibit HIV replication. This study examined the prevalence and correlates of GBV-C infection and clearance in three cohorts of pregnant women in Thailand. The study population consisted of 1,719 (1,387 HIV-infected and 332 HIV-uninfected) women from three Bangkok perinatal HIV transmission studies. Stored blood was tested for GBV-C RNA, GBV-C antibody, and if RNA-positive, genotype. Risk factors associated with the prevalence of GBV-C infection (defined as presence of GBV-C RNA and/or antibody) and viral clearance (defined as presence of GBV-C antibody in the absence of RNA) among women with GBV-C infection were examined using multiple logistic regression. The prevalence of GBV-C infection was 33% among HIV-infected women and 15% among HIV-uninfected women. GBV-C infection was independently associated (AOR, 95% CI) with an increasing number of lifetime sexual partners (referent-1 partner, 2 partners [1.60, 1.22-2.08], 3-10 partners [1.92, 1.39-2.67], >10 partners [2.19, 1.33-3.62]); injection drug use (5.50, 2.12-14.2); and HIV infection (3.79, 2.58-5.59). Clearance of GBV-C RNA among women with evidence of GBV-C infection was independently associated with increasing age in years (referent <20, 20-29 [2.01, 1.06-3.79] and ≥30 [3.18, 1.53-6.60]), more than 10 lifetime sexual partners (3.05, 1.38-6.75), and HIV infection (0.29, 0.14-0.59). This study found that GBV-C infection is a common infection among Thai women and is associated with HIV infection and both sexual and parenteral risk behaviors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| 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 teacher head, 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".