Serious toxicity associated with continuous nevirapine‐based HAART in pregnancy
Bibliographic record
Abstract
OBJECTIVE: This study was designed to determine the safety of nevirapine (NVP)-based highly active antiretroviral therapy (HAART) in a cohort of HIV-positive pregnant women. DESIGN: This was a prospective cohort study of HIV-positive pregnant women. POPULATION AND SETTING: All HIV-positive women treated with HAART during pregnancy from January 1997 to February 2004 at the British Columbia (BC) Women's Hospital in Vancouver, BC, Canada. METHODS: Demographic and clinical data were collected to compare antiretroviral drug toxicities in women treated antenatally with NVP-based or non-NVP-based HAART. Multivariate analyses were then used to investigate determinants of toxicity. RESULTS: From 1997 to 2004, 103 HIV-positive pregnant women received HAART. Equivalent numbers of women were initially treated with NVP-based (54%) and non-NVP-based (46%) HAART. The groups did not differ by clinical or demographic parameters and duration of HAART exposure was similar between groups. Toxicities necessitating treatment discontinuation were observed in 6 of 56 NVP-exposed women (2 cases each of grade 2, 3, and 4 toxicity) compared with 1 of 47 in the non-NVP-exposed women. First time use of NVP approached significance as a predictor for toxicity, with a toxicity rate of 12.5% (6/48) observed among those taking NVP for the first time (adjusted OR 2.68, 95% CI 0.49-14.6). CONCLUSION: Continuous NVP use in pregnancy resulted in a relatively higher rate of toxicity, and all cases of NVP toxicity occurred in women exposed to NVP for the first time during pregnancy.
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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 | 0.007 |
| 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 | 0.000 | 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".