Prolonged Indomethacin Exposure Is Associated With Decreased White Matter Injury Detected With Magnetic Resonance Imaging in Premature Newborns at 24 to 28 Weeks' Gestation at Birth
Bibliographic record
Abstract
OBJECTIVES: Newborns delivered before 28 weeks' gestation commonly have white matter lesions on MRI that are associated with adverse neurodevelopmental outcomes. Our objective was to determine the risk factors for MRI-detectable white matter injury in infants delivered before 28 weeks' gestation who were treated with prophylactic indomethacin. METHODS: This was a prospective cohort study conducted at the intensive care nursery at University of California San Francisco Children's Hospital. Patients included 57 premature newborns between 24 and 27 (+6 days) weeks' gestation at birth (October 1998 to October 2004). We identified perinatal and neonatal risk factors associated with moderate-severe "white matter injuries" (T1 signal abnormalities >2 mm or >3 areas of T1 abnormality) and moderate-severe "brain abnormality" (moderate-severe white matter injuries, any degree of ventriculomegaly, or severe intraventricular hemorrhage) on MRI. Infants were studied with MRI at 31.1 weeks' postmenstrual age (median). RESULTS: Moderate-severe white matter injuries were detected in 12 (21%) of 53 preterm newborns, and 20 (35%) of 57 had moderate-severe brain abnormality. Prolonged indomethacin exposure was the only risk factor independently associated with a lower risk of white matter injury or brain abnormality, even when adjusting for the presence of a hemodynamically significant PDA, gestational age at birth, prenatal betamethasone, systemic infection, and days of mechanical ventilation. CONCLUSIONS: In this observational study, a longer duration of indomethacin exposure was associated with less white matter injury in infants delivered before 28 weeks' gestation. A randomized trial of prolonged indomethacin treatment is needed to determine whether indomethacin can decrease white matter injury and neurodevelopmental abnormalities.
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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 | 0.000 | 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".