Pyramidal tract maturation after brain injury in newborns with heart disease
Bibliographic record
Abstract
OBJECTIVE: Our objective was to quantify white matter tract development in term newborns with congenital heart disease, a population at high risk for perioperative brain injury, using magnetic resonance imaging diffusion tensor tractography (DTT). METHODS: Twenty-five newborns with congenital heart disease were imaged before and after surgery, with a median of 2 weeks between serial magnetic resonance imaging examinations. DTT was performed to segment bilateral pyramidal tracts using semiautomated fiber tracking software, and manual region of interest measurements were taken for comparison. RESULTS: Significant maturational rates of increasing fractional anisotropy (median, 4.4% per week) and decreasing mean diffusivity (D(av)) (median, -2.0% per week) in the pyramidal tract were measured in infants without brain injury. Fractional anisotropy maturation rates were highest in newborns with normal scans, intermediate (median, 2.4% per week) in those with postoperative injury, and lowest (median, 0.9% per week) in those with preoperative injury, indicating a significant trend across brain injury groups (p = 0.015). D(av) maturation rates did not differ across injury groups (p = 0.15). Manual region of interest measures showed greater variability in serial measurements, and no significant differences were identified between injury groups, suggesting that DTT may provide more sensitive measures. INTERPRETATION: DTT is feasible in term newborns and may help to characterize abnormal white matter tract development following acquired brain injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".