Brain injury and development in newborns with critical congenital heart disease
Bibliographic record
Abstract
OBJECTIVE: To determine the relationship between radiologically identifiable brain injuries and delayed brain development as reflected by brain metabolic and microstructural integrity. METHODS: Term newborns with congenital heart disease (CHD) (120 preoperatively and 104 postoperatively) were studied with MRI to determine brain injury severity (BIS), microstructure reflected by fractional anisotropy (FA) and average diffusivity (Dav), and metabolism reflected by N-acetylaspartate (NAA)/choline (Cho) and lactate/Cho. Brain development is characterized by increasing NAA/Cho and white matter FA, and by decreasing Dav and lactate/Cho. RESULTS: Newly acquired brain injury was common (41% preoperative, 30% postoperative). Lower white matter FA (p = 0.005) and lower NAA/Cho (p = 0.01) were associated with increasing preoperative BIS. Higher neonatal illness severity scores (p = 0.03), lower preoperative oxygen saturation (p = 0.002), hypotension (p < 0.001), and septostomy (p = 0.002) were also predictive of higher preoperative BIS. Preoperative FA, Dav, and NAA/Cho did not predict new postoperative BIS. Increasing preoperative BIS predicted higher postoperative Dav (p = 0.002) and lactate/Cho (p = 0.008). Within the postoperative scan, new brain injuries were associated with lower white matter FA (p = 0.04). Postoperative BIS (new lesions) was associated with lower postoperative systolic (p = 0.03) and mean (p = 0.05) blood pressures. CONCLUSIONS: Brain injuries in newborns with CHD are strongly related to abnormalities of brain microstructural and metabolic brain development, especially preoperatively. Both newly acquired preoperative and postoperative brain injuries are related to potentially modifiable clinical risk factors.
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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".