Clinical Factors That Predict Optimal Neurodevelopment in Very Preterm Infants (P6.325)
Bibliographic record
Abstract
Objective: To determine neonatal clinical factors that predict above-average neurodevelopmental outcomes in preterm infants at 18 months corrected age. Background: Preterm infants are at greater risk of poor neurodevelopmental outcomes. Nevertheless, some infants perform above average on neurodevelopmental assessment. It is unknown what leads these children to thrive. Design/Methods: A cohort of 232 preterm infants (24-32 weeks gestation [GA]) was recruited prospectively from 2006 to 2013 at a tertiary-level NICU referral center. Clinical risk factors were recorded by chart review. Infants underwent MRI early in life and again at term-equivalent age. A single neuroradiologist scored brain abnormalities. 180 children (median GA 29 weeks) were assessed at 18 months corrected age with Bayley-III. 8 infants died before 18 months. Optimal neurodevelopment was defined as neurodevelopment scores >1 SD above the mean (>115) for each of the cognitive, language and motor domains. Results: Scores >115 were seen in 48, 26 and 11 children in the cognitive, language and motor domains respectively. Scores of >115 were seen in all 3 domains in 5 children. In univariate analysis, risk factors did not differ significantly between the children who scored above or below 115, regardless of the developmental domain, if they were born >29 weeks GA. The 23 infants <29 weeks GA who thrived cognitively had less patent ductus arteriosus (P=0.004), positive culture infection (P=0.01) and chronic lung disease (P=0.045). These children were also on mechanical ventilation for a shorter duration (P=0.02) and exposed to a lesser cumulative dose of morphine postnatally (P=0.001). In infants <29 weeks GA, no significant predictors were found in the language domain, but higher maternal education seemed to be beneficial for their motor skills (P=0.02). Conclusions: The avoidance of patent ductus arteriosus, confirmed infection and/or chronic lung disease appear to be beneficial mostly to preterm infants <29 weeks.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".