Stability of hepatitis B viral load during pregnancy and implications for antepartum prophylaxis: A prospective cohort study
Bibliographic record
Abstract
BACKGROUND: We examined changes in hepatitis B virus (HBV) viral loads (VLs) in pregnancy, their association with hepatitis B e antigen (HBeAg), and the associated infant outcomes. METHODS: We prospectively followed 132 mothers positive for hepatitis B surface antigen (HBsAg) and their 135 infants from 2011 to 2015 in Vancouver, British Columbia. Outcome measures included association between maternal HBeAg and high (>200,000 IU/mL) or low (≤200,000 IU/mL) HBV VL, changes in HBV VL through pregnancy, infant HBsAg status, and infant completion of the HBV vaccination series. RESULTS: Of the 91 participants with an available HBV VL, 13 (14.3%) had an HBV VL of more than 200,000 IU/mL. Of 59 participants with paired HBeAg and HBV VL in pregnancy, 6 had an HBV VL of more than 200,000 IU/mL; of interest, 2 of the 6 (33.3%) were HBeAg-negative. Thirty-eight participants had HBV VL results at both mid-trimester and delivery. For these 38 participants, Wilcoxon signed-ranks test for paired data found that an HBV VL remained stable ( p = .58). We observed no perinatal transmissions. However, 20.7% of infants did not have a documented complete HBV vaccination series, 20.0% did not have post-vaccination HBsAg testing completed, and 18% did not have anti-HBs titres measured by age 12 months. CONCLUSIONS: Our study demonstrates that HBeAg and HBV VL are not reliably predictive of each other. This supports the improved predictive value of VL measurement in pregnancy to risk stratify pregnant patients to offer antiviral treatment when indicated and further minimize the risk of perinatal transmission.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".