95: Neonatal Outcomes in Infants <29 Weeks Gestation in Relation to Maternal Hypertension and Smoking Status
Bibliographic record
Abstract
Maternal hypertension and cigarette smoking during pregnancy are associated with adverse neonatal outcomes. Paradoxically, smoking during pregnancy is associated with a reduced incidence of gestational hypertension. However, mothers who smoke during pregnancy and develop hypertension have worse pregnancy outcomes as compared to mothers who only have hypertension or non-smoking normotensive mothers. There is little data on neonatal outcomes of infants born to mothers with hypertension who also smoke. To study the outcomes of infants of mothers with hypertension who smoke. Using the Canadian Neonatal Network Database, we analyzed the outcomes of infants <29 weeks GA admitted to Canadian NICUs from 2003–2012. Infants were divided into four groups. Group 0 comprised infants of hypertensive mothers who smoked, group 1 infants of non-smoking hypertensive mothers, group 2 infants of normotensive mothers who smoked and group 3 infants of normotensive non-smoking mothers. Composite outcome of neonatal mortality or any of the major morbidities {grade 3/4 intraventricular hemorrhage (IVH), periventricular leukomalacia (PVL), retinopathy of prematurity (ROP) > stage 2, late onset sepsis (LOS) or bronchopulmonary dysplasia (BPD) was assessed using a multivariable model. Of the 12,307 eligible infants, 172 were in group 0, 1689 in group 1, 1535 in group 2 and 8911 in group 3. Adjusted ORs with 95% CIs with reference to group 3 (normotensive, non-smokers) are reported in Table 1. Infants of hypertensive mothers, whether smokers or non-smokers, were associated with higher rates of BPD. Smoking cessation campaigns during pregnancy are needed for both maternal and neonatal benefits.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".