Impact of Perioperative Brain Injury and Development on Feeding Modality in Infants With Single Ventricle Heart Disease
Bibliographic record
Abstract
Background Tube-assisted feeding in infancy is common in patients with single-ventricle physiology ( SVP ). Postnatal brain development is delayed, and injury is common, in patients with SVP . The role of brain findings in feeding outcomes remains unclear. We sought to determine the association between neonatal perioperative brain injury and postnatal brain maturation with feeding-tube dependency in patients with SVP at neonatal discharge and just before the stage-2 palliation. Methods and Results We evaluated a cohort of 48 term neonates with SVP who underwent pre- and postoperative brain magnetic resonance imaging. Perioperative brain injury and microstructural brain development were measured with diffusion tensor imaging including fractional anisotropy in white matter and apparent diffusion coefficient in gray matter. The primary outcome was defined as being 100% orally fed (binary). Of the patients 79% (38/48) were tube fed at hospital discharge, and 27% (12/45) were tube fed before stage-2 palliation. Perioperative brain injury did not differ by group. Orally fed patients had a faster rate of decrease in apparent diffusion coefficient (3%, 95% CI 1.7% to 4.6%, P<0.001) at discharge and a faster rate of increase in fractional anisotropy (1.4%, 95% CI 0.6% to 2.2%, P=0.001) at the time of stage-2 palliation compared with tube-fed patients, denoting more robust brain development. Conclusions Slower rate of postnatal brain maturation but not perioperative brain injury is associated with feeding modality in infancy. These results support the importance of brain health in optimizing feeding outcomes in patients with SVP .
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".