Cohort study showed that growth rate increment has not been enough to prevent growth retardation of preterm infants and raised concerns about unbalanced growth
Bibliographic record
Abstract
AIM: We describe the postnatal weight gain, linear and head growth trends of surviving preterm infants from 2005 to 2017. METHODS: Multicentre cohort study, including surviving preterm infants <32 weeks (n = 21 084), from the Spanish Neonatal Network database, without major congenital malformations who were less than 50 weeks postmenstrual age at discharge. Outcomes were weight gain (g/kg/day), linear and head growth (cm/week) and changes in weight, length and head circumference z-scores from birth to discharge. The study period was divided into 2005-8, 2009-11, 2012-14 and 2015-17. RESULTS: Weight gain, linear growth and head growth were slightly higher in 2015-2017 than in 2005-2008: 12.2 ± 2.6 to 13.1 ± 2.5 g/kg/day, 0.98 ± 0.6 to 1.03 ± 0.6 cm/week and 0.76 ± 0.2 to 0.77 ± 0.3 cm/week, respectively. It was associated with a decreased fall in weigh, length and head circumference z-scores from birth to discharge (-1.32 ± 0.9 to -1.01 ± 0.84, -1.38 ± 1.2 to -1.18 ± 1.2 and -0.41 ± 1.2 to -0.33 ± 1.3, respectively). CONCLUSION: Postnatal growth restriction remained a common complication of prematurity despite some increment over the last years. Growth disproportionality seemed to be worsening as weight gain was increased more than linear growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".