Contemporary Outcomes in Tetralogy of Fallot With Absent Pulmonary Valve After Fetal Diagnosis
Bibliographic record
Abstract
Background Tetralogy of Fallot with absent pulmonary valve is associated with high mortality, but it remains difficult to predict outcomes prenatally. We aimed to identify risk factors for mortality in a large multicenter cohort. Methods and Results Fetal echocardiograms and clinical data from 19 centers over a 10‐year period were collected. Primary outcome measures included fetal demise and overall mortality. Of 100 fetuses, pregnancy termination/postnatal nonintervention was elected in 22. Of 78 with intention to treat, 7 (9%) died in utero and 21 (27%) died postnatally. With median follow‐up of 32.9 months, no deaths occurred after 13 months. Of 80 fetuses with genetic testing, 46% had chromosomal abnormalities, with 22q11.2 deletion in 35%. On last fetal echocardiogram, at a median of 34.6 weeks, left ventricular dysfunction independently predicted fetal demise (odds ratio [OR], 7.4; 95% CI 1.3, 43.0; P =0.026). Right ventricular dysfunction independently predicted overall mortality in multivariate analysis (OR, 7.9; 95% CI 2.1–30.0; P =0.002). Earlier gestational age at delivery, mediastinal shift, left ventricular/right ventricular dilation, left ventricular dysfunction, tricuspid regurgitation, and Doppler abnormalities were associated with fetal and postnatal mortality, although few tended to progress throughout gestation on serial evaluation. Pulmonary artery diameters did not correlate with outcomes. Conclusions Perinatal mortality in tetralogy of Fallot with absent pulmonary valve remains high, with overall survival of 64% in fetuses with intention to treat. Right ventricular dysfunction independently predicts overall mortality. Left ventricular dysfunction predicts fetal mortality and may influence prenatal management and delivery planning. Mediastinal shift may reflect secondary effects of airway obstruction and abnormal lung development and is associated with increased mortality.
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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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".