Growth patterns by birth size of preterm children born at 24–29 gestational weeks for the first 3 years
Bibliographic record
Abstract
BACKGROUND: Concerns are prevalent about preterm infant long-term growth regarding plotting low on growth charts at discharge, stunting, underweight, high body fat and subsequent cardiometabolic morbidities. OBJECTIVES: To examine (a) longitudinal growth patterns of extremely and very preterm infants to 3 years corrected age (CA) (outcome), categorised by their birthweight for gestational age: small, appropriate and large for gestational age (SGA, AGA and LGA, respectively) (exposure); and (b) the ability of growth faltering (<-2 z-scores) to predict suboptimal cognitive scores at 3 years CA. METHODS: Post-discharge head, length, weight and weight-4-length growth patterns of the PreM Growth cohort study infants born <30 weeks and < 1500 g, who had dietitian and multi-disciplinary support before and after discharge, were plotted against the World Health Organization growth standard. Infants with brain injuries, necrotising enterocolitis and bronchopulmonary dysplasia were excluded. RESULTS: Of the included 405 infants, the proportions of infants with anthropometric measures > - 2 z-scores improved with age. The highest proportions <-2 z-scores for length (24.2%) and weight (24.0%) were at 36 gestational weeks. The proportion with small heads was low by 0 months CA (1.8%). By 3 years CA, only a few children plotted lower than -2 z-scores for length, weight-4-length and weight (<6%). After zero months CA, high weight-4-length and body mass index > + 2 z-scores were rare (2.1% at 3 years CA). Those born SGA had higher proportions with shorter heights (16.7% vs. 5.2%) and lower weights (27.8% vs. 3.5%) at 3 years CA compared to those born AGA. The ability of growth faltering to predict cognitive scores was limited (AUROC 0.42, 95% CI 0.39, 0.45 to 0.52, 95% CI 0.41, 0.63). CONCLUSIONS: Although children born <30 weeks gestation without major neonatal morbidities plot low on growth charts at 36 weeks CA most catch up to growth chart curves by 3 years CA.
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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 | 0.000 | 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 | 0.000 | 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) | 0.002 | 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".