The Role of Antiretrovirals and Drug Resistance in Vertical Transmission of HIV‐1 Infection
Bibliographic record
Abstract
Large-cohort studies in North America, Europe, and Thailand have shown that zidovudine/azidothymidine (AZT) monotherapy, given at the late stages of pregnancy, is of proven benefit in reducing mother-to-infant HIV transmission by 51% to 68%. AZT monotherapy will not be of long-term benefit for mothers because no single drug can counteract viral infection; benefits to babies will be short-lived if HIV-1 is acquired through breastfeeding after birth. Unfortunately, ongoing mutation of HIV under conditions of drug pressure allows for the evolution and selection of AZT-resistant viruses. Emergence of AZT-resistant variants in pregnant mothers (7-29%) and their infected offspring (5-21%) has been described in several studies. Drug resistance arises more frequently in those mothers who received AZT therapy before pregnancy. Recent advances in combination chemotherapy may provide alternative strategies in prevention of vertical transmission and drug resistance. Genotypic screening of the HIV-1 isolated from pregnant mothers may provide rational modifications in antiretroviral (ARV) strategies to circumvent vertical HIV transmission. This may be of advantage for resource-rich nations but not for underdeveloped nations with limited access to ARVs. Public health programs are vital to have an impact on the tragic pandemic of pediatric AIDS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".