A Retrospective Study of the Management of HIV, Hepatitis B and Hepatitis C-Positive Pregnancies in Edinburgh, UK from 1997-2002.
Bibliographic record
Abstract
STUDY AIMS: This study aims to examine management practices for HIV-positive, HBV-positive and HCV-positive pregnancies over 1997-2002 in Edinburgh, UK, and the effects the diseases have on pregnancy outcomes. RESULTS: Equally for HIV, HBV, and HCV, 50% of the diagnoses were made before pregnancy while the other 50% were detected and diagnosed through antenatal testing. Of the 17 HBV-positive pregnancies 31.6% of the women were highly infectious at delivery and 57.9% were carriers with low infectivity. Of the 17 HIV-positive pregnancies 47.1% of the women had an undetectable viral load and 17.6% were unrecorded at delivery. All 17 HIV-positive pregnancies received ART in varying regimes, 15 (88.2%) were on combination therapy, one delivered vaginally and no women breastfed. All neonates of HBV-positive mothers received immunoglobulin and vaccination and were then breastfed. There were no specific interventions for HCV. Only one study child out of the 38 pregnancies became infected, and this was with HIV. CONCLUSION: Routine screening identifies women with no obvious risk factors, and interventions are largely accepted and effective at reducing vertical transmission. HIV therapy is individually tailored and increasingly uses several agents. Moreover, there is a movement towards allowing low viral load HIV-positive women to deliver vaginally. There are no interventions recommended for HCV infectivity alone. The difficulty collecting information illustrates that no adequate tracking system of infected pregnant women exists. Recommended is the creation of a formal database that includes standardized information such as the viral load of HIV or HCV at delivery, so that outcomes of intrapartum management can be more effectively assessed. No comment can be made on virus-related pregnancy complications, as study numbers are too small for statistically valid data.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".