Invasive Procedures in Preterm Children: Brain and Cognitive Development at School Age
Bibliographic record
Abstract
BACKGROUND: Very preterm infants (born 24-32 weeks' gestation) undergo numerous invasive procedures during neonatal care. Repeated skin-breaking procedures in rodents cause neuronal cell death, and in human preterm neonates higher numbers of invasive procedures from birth to term-equivalent age are associated with abnormal brain development, even after controlling for other clinical risk factors. It is unknown whether higher numbers of invasive procedures are associated with long-term alterations in brain microstructure and cognitive outcome at school age in children born very preterm. METHODS: Fifty children born very preterm underwent MRI and cognitive testing at median age 7.6 years (interquartile range, 7.5-7.7). T1- and T2-weighted images were assessed for the severity of brain injury. Magnetic resonance diffusion tensor sequences were used to measure fractional anisotropy (FA), an index of white matter (WM) maturation, from 7 anatomically defined WM regions. Child cognition was assessed using the Wechsler Intelligence Scale for Children-IV. Multivariate modeling was used to examine relationships between invasive procedures, brain microstructure, and cognition, adjusting for clinical confounders (eg, infection, ventilation, brain injury). RESULTS: Greater numbers of invasive procedures were associated with lower FA values of the WM at age 7 years (P = .01). The interaction between the number of procedures and FA was associated with IQ (P = .02), such that greater numbers of invasive procedures and lower FA of the superior WM were related to lower IQ. CONCLUSIONS: Invasive procedures during neonatal care contribute to long-term abnormalities in WM microstructure and lower IQ.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".