The aorto‐left ventricular tunnel from a fetal perspective: Original case series and literature review
Bibliographic record
Abstract
INTRODUCTION: Aorto-left ventricular tunnel (ALVT) accounts for <0.1% of congenital heart defects. Evidence on the prognosis from a fetal perspective is limited. With this retrospective international case series, we provide information on the outcome of fetuses with ALVT. METHODS: All members of the Association for European Pediatric and Congenital Cardiology's (AEPC) fetal working group and fetal medicine units worldwide were invited for participation. We observed antenatal parameters, neonatal outcome and postnatal follow-up. Additionally, a systematic search of the literature was performed. RESULTS: Twenty fetuses with ALVT were identified in 10 participating centers (2001-2019). Fetal echocardiographic characteristics of ALVT included an increased cardiac-thorax ratio (95%), left ventricular end-diastolic diameter (90%) and a dysplastic aortic valve (90%). Extracardiac malformations were rare (5%). Eight fetuses died at a median gestational age (GA) of 21 + 6 weeks (range, 19-24): all showed signs of hydrops prior to 24 weeks or at autopsy. All others (60%, 12/2) were live-born (median GA 38 + 4, range 37-40), underwent surgery and were alive at last follow up (median 3.2 years, range 0.1-17). The literature reported 22 ALVT fetuses with similar outcome. CONCLUSIONS: In the absence of fetal hydrops, ALVT carries a good prognosis. Fetuses who survive to 24 weeks without hydrops are likely to have a good outcome.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".