Concentrations of tenofovir, lamivudine and efavirenz in mothers and children enrolled under the Option B-Plus approach in Malawi
Bibliographic record
Abstract
OBJECTIVES: To evaluate antiretroviral drug concentrations in mothers and infants enrolled under the Option B-Plus approach for the prevention of HIV mother-to-child transmission in Malawi and to assess the maternal virological response after 1 year of treatment. PATIENTS AND METHODS: Forty-seven women and 25 children were studied. Mothers were administered during pregnancy a combination of tenofovir, lamivudine and efavirenz and continued it during breastfeeding (up to 2 years) and thereafter. Drug concentrations were evaluated in mothers (plasma and breast milk) at 1 and 12 months post-partum and in infants (plasma) at 6 and 12 months of age. Drug concentrations were determined using an LC-MS/MS validated methodology. RESULTS: In breast milk, tenofovir concentrations were very low (breast milk/maternal plasma ratio = 0.08), while lamivudine was concentrated (breast milk/plasma ratio = 3) and efavirenz levels were 80% of those found in plasma. In infants, median levels at 6 months were 24 ng/mL tenofovir, 2.5 ng/mL lamivudine and 86.4 ng/mL efavirenz. At month 12, median levels were below the limit of quantification for the three drugs. No correlation was found between drug concentrations and laboratory parameters or indices of growth. HIV-RNA >1000 copies/mL was seen at month 1 in 15% of the women and at month 12 in 8.5%. Resistance was found in half of the women with detectable viral load. CONCLUSIONS: Breastfeeding infants under Option B-Plus are exposed to low concentrations of antiretroviral drugs. With this strategy, mothers had a good virological response 1 year after delivery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".