Safety of tenofovir use during pregnancy
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association of tenofovir disoproxil fumarate (TDF) use during pregnancy with early growth parameters in HIV-exposed, uninfected (HEU) infants. DESIGN: US-based prospective cohort study of HEU children to examine potential adverse effects of prenatal TDF exposure. METHODS: We evaluated the association of maternal TDF use during pregnancy with small for gestational age (SGA); low birth weight (LBW, <2.5 kg); weight-for-age z-scores (WAZ), length-for-age z-scores (LAZ), and head circumference-for-age (HCAZ) z-scores at newborn visit; and LAZ, HCAZ, and WAZ at age 1 year. Logistic regression models for LBW and SGA were fit, adjusting for maternal and sociodemographic factors. Adjusted linear regression models were used to evaluate LAZ, WAZ, and HCAZ by TDF exposure. RESULTS: Of 2029 enrolled children with maternal antiretroviral information, TDF was used by 449 (21%) HIV-infected mothers, increasing from 14% in 2003 to 43% in 2010. There was no difference between those exposed to combination regimens with vs. without TDF for SGA, LBW, and newborn LAZ and HCAZ. However, at age 1 year, infants exposed to combination regimens with TDF had significantly lower adjusted mean LAZ and HCAZ than those without TDF (LAZ: -0.17 vs. -0.03, P=0.04; HCAZ: 0.17 vs. 0.42, P=0.02). CONCLUSION: TDF use during pregnancy was not associated with increased risk for LBW or SGA. The slightly lower mean LAZ and HCAZ observed at age 1 year in TDF-exposed infants are of uncertain significance but underscore the need for additional studies of growth outcomes after TDF use 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 | 0.002 | 0.011 |
| 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".