OC25.05: Fetal cerebral blood flow and neonatal brain white matter changes in human fetuses with complex congenital heart disease
Bibliographic record
Abstract
Neurodevelopmental delay is common in infants with complex congenital heart disease (CHD) which may be linked to white matter injury occurring before and after cardiac surgery . We have previously shown that reduced fetal cerebral oxygen consumption in CHD fetuses is associated fetal brain dysmaturation. We sought to identify any relationship between cerebral blood flow and white matter changes in CHD fetuses using neonatal cranial ultrasound and fetal cardiovascular MRI. 86 CHD fetuses (mean gestation age 36.01 ± 1.4) and 40 normal controls (mean gestation age 36.9 ± 1.1) were studied using MRI and Doppler ultrasound system. We measured the middle cerebral artery and umbilical artery pulsitility index with ultrasound, superior vena cava (SVC) flow and fetal brain weight (EBW) with MRI using our previously published technique. Neonatal head ultrasound (HUS) performed after delivery was used to classify the newborn brains into three groups: 1) normal appearances, 2) increased white matter echogenicity (WME), or 3) periventricular leukomalacia (PVL). Fetal hemodynamic parameters and estimate fetal brain weight Z-Score were calculated. Extreme SVC flows were defined as SVC flow >2SD above mean: 208 ml/ min/ Kg or <2 SD below mean: 66 ml/ min/ Kg. 38% of neonates with CHD had increased WME on HUS and 10% had PVL. Elevated SVC flow was associated with a markedly increased risk of PVL (OR: 8.0, p = 0.03). In keeping with previous studies, we found smaller brains and a high incidence of WME and PVL in newborns with CHD. Abnormally high SVC flow, in keeping with “brain-sparing physiology” appears to be highly associated with PVL, suggesting that the combination of CHD and placental disease may be dangerous for the immature white matter in CHD newborns. Abnormal SVC flow by fetal cardiac MRI may be a more useful indicator of increased risk for white matter injury during late gestation, and could indicate early delivery by Caesarean section.
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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 | 0.003 |
| 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".