Impact of pregnancy on abacavir pharmacokinetics
Bibliographic record
Abstract
OBJECTIVE: To describe abacavir pharmacokinetics during pregnancy and postpartum; physiological changes during pregnancy are known to affect antiretroviral drug disposition. DESIGN: The Pediatric AIDS Clinical Trials Group P1026s study is an on-going, prospective, non-blinded pharmacokinetic study of pregnant women receiving one or more antiretroviral drugs for routine clinical care, including a cohort receiving abacavir 300 mg twice daily. METHODS: Serial plasma samples (predose, 1, 2, 4, and 6 h postdose) obtained antepartum (30-36 weeks of gestation) and again postpartum (6-12 weeks after delivery) were assayed for abacavir concentration by reversed-phase high-performance liquid chromatography. RESULTS: Antepartum evaluations were available for 25 women [mean age, 28.6 years (SD, 6); mean third-trimester weight 92 kg (SD, 35.4); and race/ethnicity 52% black, 28% Hispanic, 16% white, 4% Asian], with geometric mean abacavir area under the concentration-time curve (AUC) of 5.9 mg.h/l [90% confidence interval (CI), 5.2-6.8] and maximum plasma concentration (Cmax) of 1.9 mg/l (90% CI, 1.6-2.2). Seventeen women completed postpartum sampling, and the ratios of antepartum to postpartum AUC and Cmax were 1.04 (90% CI, 0.91-1.18) and 0.79 (90% CI, 0.65-0.98), respectively. CONCLUSIONS: Abacavir AUC during pregnancy was similar to that at 6-12 weeks postpartum and to that for non-pregnant historical controls (5.8 mg.h/l). Consequently, pregnancy does not appear to affect overall abacavir exposure significantly or to necessitate dose adjustments.
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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 | 0.005 |
| 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 | 0.001 | 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".