Perioperative cerebral hemodynamics and oxygen metabolism in neonates with single-ventricle physiology
Bibliographic record
Abstract
Congenital heart disease (CHD) patients are at risk for neurodevelopmental delay. The etiology of these delays is unclear, but abnormal prenatal cerebral maturation and postoperative hemodynamic instability likely play a role. A better understanding of these factors is needed to improve neurodevelopmental outcome. In this study, we used bedside frequency-domain near infrared spectroscopy (FDNIRS) and diffuse correlation spectroscopy (DCS) to assess cerebral hemodynamics and oxygen metabolism in neonates with single-ventricle (SV) CHD undergoing surgery and compared them to controls. Our goals were 1) to compare cerebral hemodynamics between unanesthetized SV and healthy neonates, and 2) to determine if FDNIRS-DCS could detect alterations in cerebral hemodynamics beyond cerebral hemoglobin oxygen saturation (SO 2). Eleven SV neonates were recruited and compared to 13 controls. Preoperatively, SV patients showed decreased cerebral blood flow (CBFi ), cerebral oxygen metabolism (CMRO 2i ) and SO 2; and increased oxygen extraction fraction (OEF) compared to controls. Compared to preoperative values, unstable postoperative SV patients had decreased CMRO 2i and CBFi , which returned to baseline when stable. However, SO 2 showed no difference between unstable and stable states. Preoperative SV neonates are flow-limited and show signs of impaired cerebral development compared to controls. FDNIRS-DCS shows potential to improve assessment of cerebral development and postoperative hemodynamics compared to SO 2 alone.
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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) | 0.000 | 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".