Small for gestational age at preterm birth identifies adverse neonatal outcomes more reliably than antenatal suspicion of fetal growth restriction
Bibliographic record
Abstract
Background Fetal growth restriction (FGR) is an important reason for premature delivery and a leading cause of perinatal morbidity and mortality. We aimed to evaluate whether classification as small for gestational age (SGA; <10th centile) at birth or antenatal suspicion of FGR was more strongly associated with neonatal morbidity and mortality in preterm infants.Methods A retrospective audit of infants born between 24 + 0 and 32 + 6 weeks of gestation from 2012–2019 and admitted to the Neonatal Unit at Mercy Hospital for Women (MHW). Infants were categorized according to whether FGR was listed as an antenatal complication in the medical records and whether they were SGA (<10th centile on Fenton chart) or appropriate for gestational age (AGA) at birth, and comparisons for neonatal outcomes were made.Results 371/2126 preterm infants (17.5%) had antenatal suspicion of FGR, and 166 (7.8%) were SGA at birth. No differences in any neonatal outcomes were found between infants with or without suspected FGR, except decreased intraventricular hemorrhage (IVH) in the FGR group. SGA classification was associated with increased rates of all morbidities other than IVH, including bronchopulmonary dysplasia, retinopathy of prematurity, and necrotizing enterocolitis, compared with the AGA group. Death was significantly higher in the SGA group (7.2%) compared with the AGA group (3.5%).Conclusion SGA by Fenton chart more reliably identified neonates at risk of adverse neonatal outcomes than antenatal suspicion of FGR, suggesting it is a reasonable clinical proxy. This most likely reflects the much lower tenth centile weight cutoffs on the Fenton charts compared to in-utero charts used antenatally to diagnose FGR based on ultrasound estimated fetal weight. SGA classification by Fenton approximately equates to <3rd centile on in-utero charts at our institution, therefore identifying the most severe FGR cases.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".