Infectious Diseases in Obstetrics and Gynecology 6:237-243 (I 998) (C) 1999 Wiley-Liss, Inc. Initial Multicenter Experience With Double Nucleoside Therapy for Human Immunodeficiency Virus Infection During Pregnancy
Bibliographic record
Abstract
Objective: To study maternal and neonatal effects of combination nucleoside analog therapy administered to human immunodeficiency virus (HIV)-infected pregnant women for maternal indications. Methods: A multicenter, prospective observational study was undertaken at six perinatal centers in the United States and Canada that supported regional referral programs for the treatment of HIV-infected pregnant women. Demographic, laboratory, and pregnancy outcome data were collected for 39 women whose antiretroviral treatment regimens were expanded to include more than one nucleoside analog for maternal indications. The 40 newborns were monitored at pediatric referral centers through at least three months of age to ascertain their HIV infection status. Results: For all 39 women, zidovudine (ZDV) therapy was instituted at 13.4 8.2 weeks, with a second agent (lamivudine [3TC] in 85 % of cases) being added at a mean gestational age of 17.6 weeks. Duration of therapy with two agents was 20.6+ 10.4 weeks overall, with no women stopping medications because of side effects or toxicity. No significant changes in maternal laboratory values were seen, except for an increase in mean corpuscular volume, over the course of pregnancy. No
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.015 |
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".