Can Birth Weight Standards Based on Healthy Populations Improve the Identification of Small-for-Gestational-Age Newborns at Risk of Adverse Neonatal Outcomes?
Bibliographic record
Abstract
OBJECTIVES: To develop neonatal growth standards based on (1) the entire population of live births and (2) a healthy subpopulation and compare them in identifying infants as small for gestational age and at risk of adverse neonatal outcomes. PATIENTS AND METHODS: We included all births, between 28 and 41 weeks of gestation, reported in Burgundy (France) from 2000 to 2006. Fetal deaths, multiple births, and chromosomal aberrations were excluded. We first estimated separate birth weight distributions at each week of gestation for (1) all neonates and (2) only infants born from women without maternal diseases. Small for gestational age was defined as a birth weight below the 10th percentile of the corresponding standard. We assessed the associations of small for gestational age on the basis of the alternative definitions, with mortality and major neonatal outcomes. RESULTS: We included 127 584 live births. For term newborns, small for gestational age was significantly associated with an increased risk of death with both standards. In contrast, for preterm newborns (32-36 weeks), small for gestational age was not significantly associated with mortality and morbidity. Very preterm infants (28-31 weeks) identified as small for gestational age according to the healthy-population standard were at higher risk of chronic lung disease and intraventricular hemorrhage. When using the entire-population standard, small for gestational age was associated with chronic lung disease but not intraventricular hemorrhage. The area under the receiver operating characteristic for predicting an intraventricular hemorrhage was significantly greater for small for gestational age defined with the healthy-population standard compared with small for gestational age classified with the entire-population standard. CONCLUSIONS: Neonatal growth standards based on healthy populations could improve the identification of very preterm neonates as small for gestational age and at risk of intraventricular hemorrhage.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".