Impact of Antiretroviral Drugs in Pregnant Women and Their Children in Africa: HIV Resistance and Treatment Outcomes
Bibliographic record
Abstract
The global community has committed itself to eliminating new pediatric HIV infections by 2015 and improving maternal, newborn, and child health and survival in the context of HIV. Such objectives require regimens to prevent mother-to-child transmission (pMTCT) which, while being highly efficacious, protect the efficacy of future first-line antiretroviral therapy (ART). Major obstacles to eliminating vertical transmissions globally include low rates of adherence to ART and non-completion of the 'pMTCT cascade' due to programmatic and structural challenges faced by healthcare systems in low-income countries. Providing all pregnant women with lifelong ART regardless of CD4 count/disease stage (Option B+) could be the most effective option to prevent both HIV transmission and resistance, assuming adherence is successfully maintained. This strategy is more likely to achieve sustained undetectable HIV viremia, does not involve ART interruptions, is simpler to implement, and is cost-effective. Where Option B+ is not available, options A (short course zidovudine with single-dose nevirapine and an ARV "tail") and B (combination ART during pregnancy and breastfeeding, with ART cessation after weaning in women not qualifying for ART for their own health) are also efficacious, highly cost-effective and associated with infrequent resistance selection if taken properly.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.000 |
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".