Fetal Hemodynamics, Early Survival, and Neurodevelopment in Patients With Cyanotic Congenital Heart Disease
Bibliographic record
Abstract
BACKGROUND: Fetuses with cyanotic congenital heart disease (CHD) exhibit profound fetal circulatory disturbances that may affect early outcomes. OBJECTIVES: This study sought to investigate the relationship between fetal hemodynamics and early survival and neurodevelopmental (ND) outcomes in patients with cyanotic CHD. METHODS: In this longitudinal observational study, fetuses with cyanotic CHD underwent late gestational fetal cardiovascular magnetic resonance (CMR) to measure vessel blood flow and oxygen content. Superior vena cava (SVC) flow was used as a proxy for cerebral blood flow. Primary outcomes were 18-month mortality and Bayley Scales of Infant Development-III assessment. RESULTS: A total of 144 fetuses with cyanotic CHD were assessed. By 18 months, 18 patients (12.5%) died. Early mortality was associated with reduced combined ventricular output (P = 0.01), descending aortic flow (P = 0.04), and umbilical vein flow (P = 0.03). Of the surviving patients, 71 had ND outcomes assessed. Cerebral oxygen delivery was the fetal hemodynamic variable most strongly associated with cognitive, language, and motor outcomes (P < 0.05). Fetal SVC flow was also associated with cognitive, language, and motor outcomes (P < 0.01), and it remained an independent predictor of cognitive (P = 0.002) and language (P = 0.04) outcomes after adjusting for diagnosis. Diminished SVC flow also performed better than other fetal CMR and echocardiographic predictors of cognitive ND delay (receiver-operating characteristic curve area: 0.85; SE 0.05). CONCLUSIONS: Among fetuses with cyanotic CHD, diminished fetal combined ventricular output is associated with mortality, whereas cerebral blood flow and oxygen delivery are associated with early cognitive, language, and motor development at 18 months of age. These results support the inclusion of fetal CMR to help identify patients at risk of adverse ND outcomes.
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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 | 0.003 |
| 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 | 0.001 |
| 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".