Neonatal Outcomes in Very Preterm Infants With Severe Congenital Heart Defects: An International Cohort Study
Bibliographic record
Abstract
Background Very preterm infants are at high risk of death or severe morbidity. The objective was to determine the significance of severe congenital heart defects ( CHDs ) for these risks. Methods and Results This cohort study included infants from 10 countries born from 2007–2015 at 24 to 31 weeks’ gestation with birth weights <1500 g. Severe CHDs were defined by International Classification of Diseases, Ninth Revision ( ICD‐9 ) and Tenth ( ICD‐10 ) codes and categorized as those compromising systemic output, causing sustained cyanosis, or resulting in congestive heart failure. The primary outcome was in‐hospital mortality. Secondary outcomes were neonatal brain injury, necrotizing enterocolitis, bronchopulmonary dysplasia, and retinopathy of prematurity. Adjusted and propensity score–matched odds ratios ( ORs ) were calculated. Analyses were stratified by type of CHD , gestational age, and network. A total of 609 (0.77%) infants had severe CHD and 76 371 without any malformation served as controls. The mean gestational age and birth weight were 27.8 weeks and 1018 g, respectively. The mortality rate was 18.6% in infants with CHD and 8.9% in controls (propensity score–matched OR , 2.30; 95% CI , 1.61–3.27). Severe CHD was not associated with neonatal brain injury, necrotizing enterocolitis, or retinopathy of prematurity, whereas the OR for bronchopulmonary dysplasia increased. Mortality was higher in all types, with the highest propensity score–matched OR (4.96; 95% CI, 2.11–11.7) for CHD causing congestive heart failure. While mortality did not differ between groups at <27 weeks’ gestational age, adjusted OR for mortality in infants with CHD increased to 10.9 (95% CI, 5.76–20.70) at 31 weeks’ gestational age. Rates of CHD and mortality differed significantly between networks. Conclusions Severe CHD is associated with significantly increased mortality in very preterm infants.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".