Association of neonatal outcome with birth weight for gestational age in Chinese very preterm infants: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: The neonatal outcomes across different percentiles of birth weight for gestational age are still unclear. METHODS: weeks who were admitted within 7 days after birth were included. The composite outcome was defined as mortality or any one of neonatal major morbidities, including necrotizing enterocolitis (NEC), bronchopulmonary dysplasia (BPD), severe intraventricular hemorrhage (IVH), cystic periventricular leukomalacia (cPVL), severe retinopathy of prematurity (ROP), and sepsis. Multivariable logistic regressions using generalized estimating equation approach were conducted. RESULTS: A total of 8380 infants were included with a mean GA of 30 (28-31) weeks. Of these, 1373 (16.5%) were born at less than 28 weeks, while 6997 (83.5%) had a GA between 28 and 32 weeks. Our analysis indicated that the risk of composite outcomes was negatively associated with birth weight for gestational age, and compared to the reference group, the multiple-adjusted ORs (95%CI) of composite outcomes were 4.89 (3.51-6.81) and 2.16 (1.77-2.63) for infants with birth weight for gestational less than 10th percentile and 10th -30th percentile, respectively. The ORs (95%CI) of mortality, NEC, BPD, severe ROP, and sepsis in infants with birth weight for gestational age at 10th-30th percentile were 1.94 (1.56-2.41), 1.08 (0.79-1.47), 2.48 (2.03-3.04), 2.35 (1.63-3.39), and 1.39 (1.10-1.77), respectively. CONCLUSION: Our study suggested that the risk of adverse neonatal outcomes increased significantly when the birth weight for gestational age was below the 30th percentile. Regular monitoring and early intervention are crucial for these high-risk 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".