<scp>MRI</scp> characterization of hemodynamic patterns of human fetuses with cyanotic congenital heart disease
Bibliographic record
Abstract
ABSTRACT Objectives To characterize, using magnetic resonance imaging (MRI), the distribution of blood flow and oxygen transport in human fetuses with subtypes of congenital heart disease (CHD) that present with neonatal cyanosis. Methods Blood flow was measured in the major vessels of 152 late‐gestation human fetuses with CHD and 40 gestational‐age‐matched normal fetuses, using cine phase‐contrast MRI. Oxygen saturation (SaO 2 ) was measured in the major vessels of 57 fetuses with CHD and 40 controls. Results Compared with controls, we found lower combined ventricular output in fetuses with single‐ventricle physiology, with the lowest being observed in fetuses with severe forms of Ebstein's anomaly. Obstructive lesions of the left or right heart were associated with increased flow across the contralateral side. Pulmonary blood flow was reduced in fetuses with Ebstein's anomaly, while those with Ebstein's anomaly and tricuspid atresia had reduced umbilical flow. Flow in the superior vena cava was elevated in fetuses with transposition of the great arteries, normal in fetuses with hypoplastic left heart, tetralogy of Fallot or tricuspid atresia and reduced in fetuses with Ebstein's anomaly. Umbilical vein SaO 2 was reduced in fetuses with hypoplastic left heart or tetralogy of Fallot. Ascending aorta and superior vena cava SaO 2 were reduced in nearly all CHD subtypes. Conclusions Fetuses with cyanotic CHD exhibit profound changes in the distribution of blood flow and oxygen transport, which result in changes in cerebral, pulmonary and placental blood flow and oxygenation. These alterations of fetal circulatory physiology may influence the neonatal course and help account for abnormalities of prenatal growth and development that have been described in newborns with cyanotic CHD. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.
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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 | 0.001 | 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) | 0.001 | 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".