HIV Prophylaxis in High Risk Newborns: An Examination of Sociodemographic Factors in an Inner City Context
Bibliographic record
Abstract
Background. Perinatal HIV transmission is less than 1% with antiretroviral (ARV) prophylaxis. Transmission risk appears higher in "high risk" dyads, yet this is not well defined, possibly exposing more infants to combination ARV compared with standard care. Objective. To describe characteristics of mother-infant dyads where infants received ARVs and how these characteristics relate to specific ARV regimens. Methods. Retrospective chart review of ARV-receiving newborns at St. Michael's Hospital from 2007 to 2012 (and their mothers). Numerical and categorical variables were analyzed using t-tests/ANOVA F-tests and Fisher's exact tests, respectively. Results. Maternal HIV status at delivery was as follows: 69% positive and 24% unknown. Maternal factors significantly associated with newborn-triple therapy are Canadian origin, substance abuse, unstable housing, lost custody of previous children, and sex work. Neonatal factors are child protective services involvement, NICU, and lengthier admission. Maternal factors associated with monotherapy are African origin, HIV-positive, employment, and education. Further analysis based on maternal presentation at delivery demonstrated unequal distribution of many aforementioned factors. Discussion. This cohort revealed associations between particular factors and newborn-monotherapy or triple therapy that exist, suggesting that sociodemographic factors may influence the choice of ARV regimen. Canadian perinatal HIV transmission guidelines should qualify how to risk stratify newborns and consider use of rapid HIV antibody testing.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".