Foetal echocardiographic assessment of borderline small left ventricles can predict the need for postnatal intervention
Bibliographic record
Abstract
BACKGROUND: We sought to prospectively determine foetal echocardiographic factors associated with neonatal interventions in borderline hypoplastic left ventricles. METHODS: Foetuses were included who had a left ventricle that was 2-4 standard deviations below normal for length or diameter and had forward flow across the mitral and aortic valves. Factors associated with an intervention in the first month of life or no need for intervention were sought using univariate and multivariate logistic regression models. RESULTS: From 2005 to 2008, 47 foetuses meeting the criteria had an additional diagnosis (+foetal coarctation/+transverse arch hypoplasia): atrioventricular septal defect 7 (+2/+0), double outlet right ventricle 2 (+0/+0), Shone's complex 19 (+9/+4), and ventricular disproportion 19 (+13/+11; 4 both). There were seven pregnancies terminated, three foetal demises, and five had compassionate care. There were 32 livebirths that either had a biventricular repair (n = 20, n = 2 dead), univentricular palliation (n = 2, both alive), or no intervention (n = 9). Overall survival of livebirths to 6 months of age was 79%. Factors associated with early intervention on first foetal echocardiogram were: obstructed or retrograde arch flow (p = 0.08, odds ratio 3.3), coarctation (p = 0.05, odds ratio 11.4), and left ventricle outflow obstruction (p = 0.05, odds ratio 12.5). Neonatal factors included: Shone's diagnosis (p = 0.02, odds ratio 4.9), bicuspid aortic valve (p = 0.005, odds ratio 11.7), and larger tricuspid valve z-score (p = 0.05, odds ratio 3.6). A neonatal factor associated with no intervention was a larger mitral valve z-score (mean 23.8 versus 24.2 intervention group, p = 0.04, odds ratio 2.8). DISCUSSION: The need for early intervention in foetuses with borderline hypoplastic left ventricle can be predicted by foetal echocardiography.
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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 | 0.009 |
| 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".