Incidence, predictors and outcomes of congenital diaphragmatic hernia: a population-based study of 32 million births in the United States
Bibliographic record
Abstract
OBJECTIVES: To evaluate the incidence, risk factors and neonatal outcomes associated with a congenital diaphragmatic hernia (CDH). STUDY DESIGN: We conducted a population-based cohort study using the CDC's Linked Birth-Infant Death and Fetal Death data files on all births and foetal deaths in USA between 1995 and 2002. We estimated the yearly incidence of CDH and measured its adjusted effect on various outcomes using unconditional logistic regression analysis. RESULTS: About 32,145,448 births during the 8-year study period met the study's inclusion criteria. The incidence of CDH was 1.93/10,000 births. Risk factors for the development of CDH included foetal male gender [OR 1.12, 95% CI: 1.06, 1.17], maternal age beyond 40 [OR 1.51, 95% CI: 1.26, 1.80], Caucasian ethnicity [OR 1.15, 95% CI: 1.10, 1.21], smoking [OR 1.34, 95% CI: 1.22, 1.46] and alcohol use during pregnancy [OR 1.37, 95% CI: 1.05, 1.79]. As compared to foetuses with no CDH, foetuses with CDH were at an increased risk of preterm birth [OR 2.90, 95% CI: 2.72, 3.11], intrauterine growth restriction [OR 3.84, 95% CI: 3.51, 4.18], stillbirth [OR 9.65, 95% CI: 8.20, 11.37] and overall infant death [OR: 94.80, 95% CI: 88.78, 101.23]. The 1-year mortality was 45.89%. CONCLUSION: Congenital diaphragmatic hernia is strongly associated with an increased risk of adverse pregnancy, foetal and neonatal outcomes. These findings may be helpful in counselling pregnancies affected by CDH, and may aid in the understanding of the burden of this condition at the public health level.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".