Abstract 17303: Longitudinal Cerebral Oxygen Metabolism in Congenital Heart Disease
Bibliographic record
Abstract
Background: Brain growth differences are apparent between different types of cyanotic congenital heart disease, but the underlying mechanism remains unclear. Here, we explored and characterized longitudinal cerebral hemodynamic and oxygen metabolism profiles and their relationships to brain growth patterns in infants with single ventricle physiologies (SV) and transposition of the great arteries (TGA). We hypothesized that there are marked differences in cerebral oxygen metabolism in those with SV compared with TGA. Methods: Cerebral blood flow (CBF), oxygen delivery (CDO2) and consumption (CVO2) and brain growth were measured in 103 term newborns with SV and TGA using MRI at pre- and post-surgery and at follow-up. We measured whole brain size by segmenting a 3D steady state free precession acquisition. Cerebral blood flow was measured using phase contrast imaging of the neck vessels and cerebral venous blood oxygen saturation was derived from T2 oximetry of the superior sagittal sinus. TGAs were divided into those with and without ventricular septums. Results: CBF profiles were similar between the 3 lesion groups. Cerebral oxygen delivery trends increased but were not significantly different between cardiac groups. We observed that this may be mediated by different mechanisms: an increase in arterial saturation in TGAs, and an increase in hemoglobin concentration in SVs. Cerebral oxygen consumption in SV infants remained low (p = 0.54) while that of TGA increased over time (TGA IVS p < 0.001; TGA VSD p <0.001) (Fig. 1), mediated by an unchanging oxygen extraction fraction in SVs (p = 0.59). The SV cerebral oxygen consumption profile aligned with their declining brain weight z-score trajectory. Conclusions: In conclusion, there are characteristic differences in hemodynamic adaptations between SVs and TGAs. Changes in oxygen metabolism may be facilitating brain growth trajectories. This informs us of possible mechanisms involved during a time of critical brain 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 | 0.001 |
| 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".