Brain Volume and Metabolism in Fetuses With Congenital Heart Disease
Bibliographic record
Abstract
BACKGROUND: Adverse neurodevelopmental outcome is an important source of morbidity in children with congenital heart disease (CHD). A significant proportion of newborns with complex CHD have abnormalities of brain size, structure, or function, which suggests that antenatal factors may contribute to childhood neurodevelopmental morbidity. METHODS AND RESULTS: Brain volume and metabolism were compared prospectively between 55 fetuses with CHD and 50 normal fetuses with the use of 3-dimensinal volumetric magnetic resonance imaging and proton magnetic resonance spectroscopy. Fetal intracranial cavity volume, cerebrospinal fluid volume, and total brain volume were measured by manual segmentation. Proton magnetic resonance spectroscopy was used to measure the cerebral N-acetyl aspartate: choline ratio (NAA:choline) and identify cerebral lactate. Complete fetal echocardiograms were performed. Gestational age at magnetic resonance imaging ranged from 25 1/7 to 37 1/7 weeks (median, 30 weeks). During the third trimester, there were progressive and significant declines in gestational age-adjusted total brain volume and intracranial cavity volume in CHD fetuses relative to controls. NAA:choline increased progressively over the third trimester in normal fetuses, but the rate of rise was significantly slower (P<0.001) in CHD fetuses. On multivariable analysis adjusted for gestational age and weight percentile, cardiac diagnosis and percentage of combined ventricular output through the aortic valve were independently associated with total brain volume. Independent predictors of lower NAA:choline included diagnosis, absence of antegrade aortic arch flow, and evidence of cerebral lactate (P<0.001). CONCLUSIONS: Third-trimester fetuses with some forms of CHD have smaller gestational age- and weight-adjusted total brain volumes than normal fetuses and evidence of impaired neuroaxonal development and metabolism. Hemodynamic factors may play an important role in this abnormal development.
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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 | 0.002 |
| 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) | 0.000 | 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 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".