Implications for quantifying early life growth trajectories of term‐born infants using INTERGROWTH‐21st newborn size standards at birth in conjunction with World Health Organization child growth standards in the postnatal period
Bibliographic record
Abstract
BACKGROUND: The INTERGROWTH-21st sex and gestational age (GA) specific newborn size standards (IG-NS) are intended to complement the World Health Organization Child Growth Standards (WHO-GS), which are not GA-specific. We examined the implications of using IG-NS at birth and WHO-GS at postnatal ages in longitudinal epidemiologic studies. OBJECTIVES: The aim of this study was to quantify the extent to which standardised measures of newborn size and growth are affected when using WHO-GS versus IG-NS at birth among term-born infants. METHODS: )]. We used Bland-Altman plots to compare continuous indices and Kappa statistic to compare categorical indicators. RESULTS: At birth, mean LAZ, WAZ and HCAZ, and the prevalence of undernutrition were most similar among newborns between 39 and 40 weeks of GA when using WHO-GS versus IG-NS. However, anthropometric indices were systematically lower among early-term infants and higher among late-term infants when using WHO-GS versus IG-NS. Early-term and late-term infants demonstrated relatively faster and slower growth, respectively, when using WHO-GS versus IG-NS, with the direction and magnitude of differences varying between anthropometric indices. Individual-level differences in attained size and growth, when using WHO-GS versus IG-NS, were greater than 0.2 SD in magnitude for >60% of infants across all anthropometric indices. CONCLUSIONS: Using IG-NS at birth with WHO-GS postnatally is acceptable for full-term infants but may give a misleading interpretation of growth trajectories among early- and late-term 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 | 0.018 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".