Interaction of chorioamnionitis at term with maternal, fetal and obstetrical factors as predictors of neonatal mortality: a population-based cohort study
Bibliographic record
Abstract
Abstract Background Chorioamnionitis is a frequent complication of pregnancy and is known to be associated with serious adverse post-natal outcomes including death. However, the assessment of fetal well-being in labor in the context of chorioamnionitis is often challenging because of fetal tachycardia. Identifying specific risk factors for adverse neonatal outcomes in the context of chorioamnionitis could therefore be of paramount importance. This study aimed to determine if maternal and fetal risk factors for increased neonatal mortality and early neonatal mortality are modified in the context of chorioamnionitis in term pregnancies. Methods A retrospective population-based cohort study using the United States birth/infant death public file from 2011 to 2013 was performed, including all live births at 37 weeks gestation and beyond. Interaction between chorioamnionitis and maternal demographic variables as well as labor and delivery potential risk factors were analyzed for association with neonatal death (< 28 days) and early neonatal death (< 7 days) using multivariate logistic regressions. Results Among 9,034,428 live births, the prevalence of chorioamionitis was 1.29% (95% CI 1.28–1.30%). The incidence of neonatal death and early neonatal death were 0.09 and 0.06% in the chorioamnionitis group versus 0.06 and 0.04% in the no chorioamnionitis group ( p = 0.0003 and < 0.0001), respectively. Smoking was significantly associated with neonatal death and early neonatal death in the context of chorioamnionitis (OR 2.44, CI:1.34–4.43/ 2.36 CI:1.11–5.01) but was either less strongly or not associated in the absence of chorioamnionitis (OR 1.24, CI:1.14–1.35/0.93, CI:0.82–1.05). The association between gestational age (37 weeks compared to 39 weeks) and neonatal death was more important in the context of chorioamnionitis (OR = 3.19, CI: 1.75–5.82 versus 1.63, CI: 1.49–1.79). Multivariate analysis identified the following risk factors for neonatal death and/or early neonatal death: low maternal education, extreme maternal age, obesity (BMI > 35 kg/m 2 ), late or no prenatal care, diabetes, meconium-stained amniotic fluid, gestational ages other than 39 weeks, neonatal weight < 2500 g and delivery by vacuum or caesarian. Conclusions Smoking as well as early term have a positive interaction with chorioamnionitis for the risk of neonatal mortality. This should be taken into account when counseling pregnant women and managing laboring pregnant women with suspected chorioamnionitis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".