Missed Opportunities for Prevention of Perinatal Transmission of Hepatitis B: A Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Perinatal transmission of hepatitis B virus (HBV) can occur despite postexposure prophylaxis (PEP). Recent literature suggests that antiviral treatment during pregnancy when maternal HBV DNA levels are elevated can further decrease vertical transmission. However, HBV DNA screening is not routinely performed antenatally. OBJECTIVE: To determine the rates of HBV prevalence and perinatal transmission in an antenatal cohort. METHODS: A retrospective review of public health records (December 2008 to December 2010) was performed for both mothers and newborns. RESULTS: A total of 725 mother-infant pairs were included. Of these, 574 of 715 (80%) women had antenatal hepatitis B e antigen (HBeAg) testing performed, and 127 of 574 (22%) were HBeAg positive (HBeAg+). Of babies born to hepatitis B surface antigen-positive (HBsAg+) mothers, only 573 of 725 (79%) received complete PEP. In addition, 172 of 725 (24%) infants did not receive post-PEP blood testing or were lost to follow-up. Of the 552 infants with results available, seven cases (1.3%) of mother-to-child HBV transmission were observed, six of which involved infants born to HBeAg+ women. CONCLUSIONS: Our findings suggest that routine HBeAg screening could identify a subset of mother-infant pairs among HBsAg+ pregnant women who are at higher risk for vertical HBV transmission. Determination of viral load in expectant HBeAg+ mothers may provide more precise insight into HBV transmission to their infants.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".