Neurodevelopmental outcomes and in-utero antiretroviral exposure in HIV-exposed uninfected children
Bibliographic record
Abstract
OBJECTIVES: To assess and compare neurodevelopmental disorders in HIV-exposed uninfected (HEU) and HIV-unexposed uninfected (HUU) children in British Columbia, Canada. To determine associations between these outcomes and in-utero exposure to antiretroviral drugs. DESIGN: Retrospective controlled cohort study. METHODS: Data were collected on 446 HEU children and 1323 HUU children (matched ∼1 : 3 for age, sex, and geocode) born between 1990 and 2012. Multivariable logistic regressions determined odds ratios of neurodevelopmental disorder diagnoses. RESULTS: HEUs had three times higher odds of being born preterm (P < 0.0001), and a more than two-fold increase in odds for autism, disturbance of emotions, hyperkinetic syndrome, and developmental delay compared with matched HUUs (P < 0.02) in unadjusted analysis. This association was reduced [adjusted neurodevelopmental disorder odds ratio (AOR) = 1.67; 95% confidence interval: 1.12-2.48; P = 0.011] after adjusting for maternal substance use and/or smoking (children born after April 2000). Regardless of antiretroviral exposure type (i.e. none, treatment with one or multiple drug classes), HEUs had higher odds of any neurodevelopmental disorders compared with matched HUUs; however, there was no evidence suggesting any specific classes of antiretroviral drugs or exposure durations increased their likelihood of neurodevelopmental disorders. CONCLUSION: The results suggest no adverse associations between antiretroviral drugs and neurodevelopmental disorders within antiretroviral-exposed HEU children in our cohort. Prevalence of neurodevelopmental disorders is higher in HEUs; however, maternal substance use plays a role, as could other environmental factors not captured. These findings highlight a need for holistic support for pregnant women as well as careful developmental monitoring of HEUs past infancy, and access to early interventions, particularly among those born preterm and those exposed to addictive substances.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".