Monitoring the Postnatal Growth of Preterm Infants: A Paradigm Change
Bibliographic record
Abstract
There is no consensus regarding how the growth of preterm infants should be monitored or what constitutes their ideal pattern of growth, especially after term-corrected age. The concept that the growth of preterm infants should match that of healthy fetuses is not substantiated by data and, in practice, is seldom attained, particularly for very preterm infants. Hence, by hospital discharge, many preterm infants are classified as postnatal growth-restricted. In a recent systematic review, 61 longitudinal reference charts were identified, most with considerable limitations in the quality of gestational age estimation, anthropometric measures, feeding regimens, and how morbidities were described. We suggest that the correct comparator for assessing the growth of preterm infants, especially those who are moderately or late preterm, is a cohort of preterm newborns (not fetuses or term infants) with an uncomplicated intrauterine life and low neonatal and infant morbidity. Such growth monitoring should be comprehensive, as recommended for term infants, and should include assessments of postnatal length, head circumference, weight/length ratio, and, if possible, fat and fat-free mass. Preterm postnatal growth standards meeting these criteria are now available and may be used to assess preterm infants until 64 weeks' postmenstrual age (6 months' corrected age), the time at which they overlap, without the need for any adjustment, with the World Health Organization Child Growth Standards for term newborns. Despite remaining nutritional gaps, 90% of preterm newborns (ie, moderate to late preterm infants) can be monitored by using the International Fetal and Newborn Growth Consortium for the 21st Century Preterm Postnatal Growth Standards from birth until life at home.
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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 | 0.149 | 0.147 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.009 | 0.024 |
| Open science | 0.012 | 0.008 |
| Research integrity | 0.013 | 0.029 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".