The Risks of Adverse Neonatal Outcome Among Preterm Small for Gestational Age Infants According to Neonatal Versus Fetal Growth Standards
Bibliographic record
Abstract
OBJECTIVE: To evaluate neonatal and fetal growth standards in determining the impact of small for gestational age (SGA) on neonatal mortality and morbidity. DESIGN: A hospital-based cohort study of infants born in a regional tertiary care center and admitted to the neonatal intensive care unit. SETTING AND PARTICIPANTS: A total of 1267 singleton neonates of <34 weeks gestational age, without any congenital anomalies, born between January 1, 1993 and December 31, 2001. OUTCOME MEASURES: Each outcome variable including mortality, respiratory distress syndrome, bronchopulmonary dysplasia, intraventricular hemorrhage (IVH), periventricular leukomalacia, and necrotizing enterocolitis was related to growth status as defined by fetal and neonatal growth standards after adjustment for potential confounders. RESULTS: The number of SGA infants was 11.6% (n = 147) of the study population according to neonatal growth standards, but it was increased to 23.3% (n = 295) when fetal growth standards were used. According to fetal growth standards, when SGA was compared with appropriate for gestational age infants, it was associated with an increased risk of respiratory distress syndrome (odds ratio [OR] 1.40; 95% confidence interval [CI] 1.00-1.95), bronchopulmonary dysplasia (OR 2.18; 95% CI 1.33-3.59), IVH (OR 1.67; 95% CI 1.13-2.45), and retinopathy of prematurity (OR 3.88; 95% CI 2.33-6.48). However, only neonatal mortality (OR 3.64; 95% CI 1.64-8.09), retinopathy of prematurity (OR 5.38; 95% CI 2.87-10.90), and necrotizing enterocolitis (OR 2.47; 95% CI 1.21-5.07) were positively associated with SGA when using neonatal growth standards. CONCLUSIONS: Compared with the neonatal growth standards, the fetal growth standards are better in identifying increased risk of respiratory morbidity and IVH among preterm SGA 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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".