Neurodevelopmental outcomes of premature infants treated with <scp>l</scp>‐arginine for prevention of necrotising enterocolitis
Bibliographic record
Abstract
AIM: This study aimed to compare the long-term neurodevelopmental outcomes at 36 months adjusted age in preterm infants (birth weight < or = 1250 gm) who received supplementation with L-arginine during the first 28 days of life with controls. METHODS: Surviving infants enrolled in a randomised control study of L-arginine supplementation were prospectively followed longitudinally to determine their neurodevelopmental outcomes at 36 months of adjusted age. Neurologic examination and neurodevelopmental assessments were performed by examiners who were unaware of the original treatment assignments. RESULTS: A total of 132 children (95% of survivors) were evaluated at 36 months adjusted age. In the group given L-arginine, 5 of 61 (8.1%) had major neurodevelopmental disabilities, defined as the presence of one or more of cerebral palsy, cognitive delay (cognitive index <70), bilateral blindness or bilateral hearing loss requiring hearing aids as compared with 9 of 71 (12.6%) in the placebo group (relative risk, 0.64; 95 % confidence interval, 0.22-1.82; P= 0.40). CONCLUSIONS: There is no increase in neurodevelopmental disability in preterm infants who received L-arginine supplementation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".