Abstract 19647: The Evolution of Cardiac Output and Cerebral Blood Flow in the Perinatal Transition in Hypoplastic Left Heart Syndrome: a Longitudinal Study
Bibliographic record
Abstract
Background: Cardiovascular adaptation through the perinatal transition has not been previously explored in fetuses with hypoplastic left heart syndrome (HLHS). We sought to investigate the evolution of cardiac output in HLHS from late gestation through the perinatal period with comparison to healthy fetuses. As fetal HLHS has progressive middle cerebral arterial (MCA) Doppler changes suggestive of brain sparing, we further examined the impact of the transition on MCA blood flow. We hypothesized ductal patency with falling pulmonary vascular resistance after birth in HLHS could lead to cerebral steal. Methods: We prospectively recruited 9 healthy and 11 pregnancies complicated by fetal HLHS. Echocardiograms were performed before birth at ≥37 weeks gestation and after birth at 4-6, 20-24, and 40-48 hours (all newborns), and 3-5 days (HLHS neonates only). Ventricular stroke volumes (SV) were determined using pulse Doppler and semilunar valve diameters, and combined cardiac output (CCO) was calculated (SV x heart rate (HR)). MCA pulsatility index (PI) was determined using the peak systolic, end diastolic and mean velocities. Results: In late gestation, the CCO was similar between groups (HLHS mean 404 ± 91 vs. control 373 ± 96cc/kg/min). After birth, there was a trend towards higher CCO in HLHS at 4-6 and 20-24 hours (p= 0.06), which reached significance at 48 hours (587±155 vs controls 402±73 cc/kg/min, p=0.03). The CCO was highest in HLHS at 3-5 days (672 ± 117cc/kg/min, p Conclusions: HLHS newborns significantly increase their cardiac output in the perinatal transition, particularly from 48 hours onward, through both increased HR and SV. While just prior to birth the MCA PI in HLHS suggests brain sparing, a reverse finding is observed after birth, which could reflect increased CCO and/or cerebral steal. This could be a period of cerebral vulnerability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".