In Utero Antiretroviral Exposure and Risk of Neurodevelopmental Problems in HIV-Exposed Uninfected 5-Year-Old Children
Bibliographic record
Abstract
Studies have observed neurodevelopmental (ND) challenges among young children perinatally HIV-exposed yet uninfected (CHEU) with in utero antiretroviral (ARV) exposure, without clear linkage to specific ARVs. Atazanavir (ATV) boosted with ritonavir has been a preferred protease inhibitor recommended for pregnant women, yet associations of ATV with ND problems in CHEU have been reported. Studies among early school-age children are lacking. The pediatric HIV/AIDS cohort study (PHACS) surveillance monitoring for antiretroviral therapy (ART) toxicities (SMARTT) study evaluated 5-year-old monolingual English-speaking CHEU using the behavior assessment system for children, Wechsler preschool and primary scales of intelligence, and test of language development-primary. A score ≥1.5 standard deviations worse than population norms defined a signal within each domain. Analyses of risk for signals were stratified by timing of any ARV initiation. Associations between ARV exposure and risk of ND signals were assessed using proportional odds models, adjusting for confounders. Among 230 children exposed to ARVs at conception, 15% had single and 8% had multiple ND problems; ATV exposure was not associated with higher risk of signals [adjusted cumulative odds ratio (cOR) = 0.66, confidence interval (CI): 0.28-1.56]. However, among 461 children whose mothers initiated ARVs during pregnancy, 21% had single and 12% had multiple ND problems; ATV exposure was associated with higher risk of signals (cOR = 1.70, CI: 0.82-3.54). The specific regimen tenofovir/emtricitabine/ATV was associated with higher risk (cOR = 2.31, CI: 1.08-4.97) relative to regimens using a zidovudine/lamivudine backbone combined with non-ATV ARVs. It remains important to monitor neurodevelopment of CHEU during early childhood and investigate the impact and the role of timing of in utero exposure to specific ARVs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".