Higher Hospitalization Rates in Children Born HIV-exposed Uninfected in British Columbia, Canada, Between 1990 and 2012
Bibliographic record
Abstract
BACKGROUND: Compared with children who are HIV-unexposed and uninfected (CHUU), children who are HIV-exposed and uninfected (CHEU) experience more clinical complications. We investigated hospitalizations among CHEU by antenatal antiretroviral therapy (ART) exposure, in British Columbia, Canada. METHODS: This retrospective controlled cohort study used administrative health data from 1990 to 2012. CHEU and CHUU were matched 1:3 for age, sex and maternal geographical area of residence. We determined adjusted odds ratios (aORs) via conditional logistic regression, adjusting for maternal risk factors. RESULTS: A total of 446 CHEU and 1333 CHUU were included. Compared with CHUU, more CHEU experienced one or more lifetime hospitalization (47.3% vs. 29.8%), one or more neonatal hospitalization (40.4% vs. 27.6%), and any intensive care unit admission (28.5% vs. 9.2%). In adjusted analyses, CHEU experienced higher odds of any lifetime hospitalization (aOR 2.30, 95% confidence interval 1.81-2.91) and neonatal hospitalization (aOR 2.14, 95% confidence interval 1.68-2.73), compared with CHUU. There was, however, no difference in infection-related hospitalizations (9.0% vs. 7.5%), which were primarily respiratory tract infections among both CHEU and CHUU. CHEU whose mothers-initiated ART preconception showed lower odds of infection-related hospitalizations than children whose mothers initiated ART during pregnancy or received no ART. CONCLUSIONS: CHEU experienced increased odds of hospitalization relative to CHUU. A substantial number of CHEU hospitalizations occurred within the neonatal period and were ICU admissions. Initiating ART preconception may reduce the risk of infection-related hospitalizations. These findings reinforce the benefit of ART in pregnancy and the need for ongoing pediatric care to reduce hospitalizations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".