Transplacental Fetal Treatment Improves the Outcome of Prenatally Diagnosed Complete Atrioventricular Block Without Structural Heart Disease
Bibliographic record
Abstract
BACKGROUND: Untreated isolated fetal complete atrioventricular block (CAVB) has a significant mortality rate. A standardized treatment approach, including maternal dexamethasone at CAVB diagnosis and beta-stimulation for fetal heart rates <55 bpm, has been used at our institutions since 1997. The study presents the impact of this approach. METHODS AND RESULTS: Thirty-seven consecutive cases of fetal CAVB since 1990 were studied. Mean age at diagnosis was 25.6+/-5.2 gestational weeks. In 33 patients (92%), CAVB was associated with maternal anti-Ro/La autoantibodies. Patients were separated into those diagnosed between 1990 and 1996 (group 1; n=16) and those diagnosed between 1997 and 2003 (group 2; n=21). The 2 study groups were comparable in the clinical presentation at CAVB diagnosis but did differ in prenatal management (treated patients: group 1, 4/16; group 2, 18/21; P<0.0001). Overall, 22 fetuses were treated, 21 with dexamethasone and 9 with beta-stimulation for a mean of 7.5+/-4.5 weeks. Live-birth and 1-year survival rates of group 1 were 80% and 47%, and these improved to 95% for group 2 patients (P<0.01). The 21 patients treated with dexamethasone had a 1-year survival rate of 90%, compared with 46% without glucocorticoid therapy (P<0.02). Immune-mediated conditions (myocarditis, hepatitis, cardiomyopathy) resulting in postnatal death or heart transplantation were significantly more common in untreated anti-Ro/La antibody-associated pregnancies compared with patients treated with steroids (0/18 versus 4/9 live births; P=0.007). CONCLUSIONS: A standardized treatment approach, including transplacental fetal administration of dexamethasone and beta-stimulation at heart rates <55 bpm, reduced the morbidity and improved the outcome of isolated fetal CAVB.
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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) | 0.001 | 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".