Effect of chorioamnionitis on brain development and injury in premature newborns
Bibliographic record
Abstract
OBJECTIVE: The association of chorioamnionitis and noncystic white matter injury, a common brain injury in premature newborns, remains controversial. Our objectives were to determine the association of chorioamnionitis and postnatal risk factors with white matter injury, and the effects of chorioamnionitis on early brain development, using advanced magnetic resonance imaging. METHODS: Ninety-two preterm newborns (24-32 weeks gestation) were studied at a median age of 31.9 weeks and again at 40.3 weeks gestation. Histopathological chorioamnionitis and white matter injury were scored using validated systems. Measures of brain metabolism (N-acetylaspartate/choline and lactate/choline) on magnetic resonance spectroscopy, and microstructure (average diffusivity and fractional anisotropy) on diffusion tensor imaging were calculated from predefined brain regions. RESULTS: Thirty-one (34%) newborns were exposed to histopathological chorioamnionitis, and 26 (28%) had white matter injury. Histopathological chorioamnionitis was not associated with an increased risk of white matter injury (relative risk: 1.2; p = 0.6). Newborns with postnatal infections and hypotension requiring therapy were at higher risk of white matter injury (p < 0.03). Adjusting for gestational age at scan and regions of interest, histopathological chorioamnionitis did not significantly affect brain metabolic and microstructural development (p > 0.1). In contrast, white matter injury was associated with lower N-acetylaspartate/choline (-8.9%; p = 0.009) and lower white matter fractional anisotropy (-11.9%; p = 0.01). INTERPRETATION: Histopathological chorioamnionitis does not appear to be associated with an increased risk of white matter injury on magnetic resonance imaging or with abnormalities of brain development. In contrast, postnatal infections and hypotension are associated with an increased risk of white matter injury in the premature newborn.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".