Neonatal outcome of small for gestational age infants born at 26–33 weeks’ gestation in Chinese neonatal intensive care units
Bibliographic record
Abstract
Background: Rate and outcomes of small for gestational age (SGA) infants admitted to Chinese neonatal intensive care units (NICU) has been poorly demonstrated. We aimed to describe the rate and outcomes of SGA preterm infants in Chinese NICU, and to evaluate the association of SGA status with neonatal outcomes in different gestational age (GA) and birth weight percentile groups.Methods: This cohort study included all infants born at 26–33 weeks’ gestation and admitted to 25 tertiary Chinese NICUs from April 2015 to May 2018. SGA was defined as a birthweight <10th percentile for GA based on the Chinese neonatal birth weight curve.Results: A total of 24,596 infants were included, and 1,867 (7.6%) infants were SGA. SGA infants had significantly higher rates of death or any major morbidity (29.8% vs. 20.5%), mortality (7.0% vs. 4.1%), bronchopulmonary dysplasia (BPD, 17.6% vs. 9.8%), necrotizing enterocolitis (NEC, 4.8% vs. 3.2%) and sepsis (7.3% vs. 4.8%) than non-SGA infants. SGA status was independently associated with increased risk of death or any major morbidity [adjusted odds ratio: 2.37 (2.08–2.71)] as well as increased risks of death, BPD, ROP, death or BPD, death or ROP, NEC and sepsis. The increased risks of adverse outcomes for SGA infants existed across GA groups. The risks of adverse outcomes were highest among infants with a birthweight <3rd percentile.Conclusions: SGA contributes significantly to adverse neonatal outcomes. Specific attentions are warranted when caring for SGA 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".