Risk Factors for Mortality and Circulatory Outcome Among Neonates Prenatally Diagnosed With Ebstein Anomaly or Tricuspid Valve Dysplasia: A Multicenter Study
Bibliographic record
Abstract
Background In a recent multicenter study of perinatal outcome in fetuses with Ebstein anomaly or tricuspid valve dysplasia, we found that one third of live‐born patients died before hospital discharge. We sought to further describe postnatal management strategies and to define risk factors for neonatal mortality and circulatory outcome at discharge. Methods and Results This 23‐center, retrospective study from 2005 to 2011 included 243 fetuses with Ebstein anomaly or tricuspid valve dysplasia. Among live‐born patients, clinical and echocardiographic factors were evaluated for association with neonatal mortality and palliated versus biventricular circulation at discharge. Of 176 live‐born patients, 7 received comfort care, 11 died <24 hours after birth, and 4 had insufficient data. Among 154 remaining patients, 38 (25%) did not survive to discharge. Nearly half (46%) underwent intervention. Mortality differed by procedure; no deaths occurred in patients who underwent right ventricular exclusion. At discharge, 56% of the cohort had a biventricular circulation (13% following intervention) and 19% were palliated. Lower tricuspid regurgitation jet velocity (odds ratio [OR], 2.3 [1.1–5.0], 95% CI, per m/s; P =0.025) and lack of antegrade flow across the pulmonary valve (OR, 4.5 [1.3–14.2]; P =0.015) were associated with neonatal mortality by multivariable logistic regression. These variables, along with smaller pulmonary valve dimension, were also associated with a palliated outcome. Conclusions Among neonates with Ebstein anomaly or tricuspid valve dysplasia diagnosed in utero, a variety of management strategies were used across centers, with poor outcomes overall. High‐risk patients with low tricuspid regurgitation jet velocity and no antegrade pulmonary blood flow should be considered for right ventricular exclusion to optimize their chance of survival.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".