Late gestation predictors of a postnatal biventricular circulation after fetal aortic valvuloplasty
Bibliographic record
Abstract
OBJECTIVES: Fetal aortic valvuloplasty (FAV) for severe aortic stenosis (AS) has shown promise in averting progression to hypoplastic left heart syndrome. After FAV, predicting which fetuses will achieve a biventricular (BiV) circulation after birth remains challenging. Identifying predictors of postnatal circulation on late gestation echocardiography will improve parental counseling. METHODS: Liveborn patients who underwent FAV and had late gestation echocardiography available were included (2000-2017, n = 96). Multivariable logistic regression and classification and regression tree analysis were utilized to identify independent predictors of BiV circulation. RESULTS: Among 96 fetuses, 50 (52.1%) had BiV circulation at the time of neonatal discharge. In multivariable analysis, independent predictors of biventricular circulation included left ventricular (LV) long axis z-score (OR 3.2, 95% CI 1.8-5.7, p < 0.001), LV ejection fraction (OR 1.3, 95% CI 1.0-1.8, p = 0.023), anterograde aortic arch flow (OR 5.0, 95% CI 1.2-20.4, p = 0.024), and bidirectional or right-to-left foramen ovale flow (OR 4.6, 95% CI 1.4-15.8, p = 0.015). CONCLUSION: Several anatomic and physiologic parameters in late gestation were found to be independent predictors of BiV circulation after FAV. Identifying these predictors adds to our understanding of LV growth and hemodynamics after FAV and may improve parental counseling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".