Bibliographic record
Abstract
OBJECTIVES: To explore the technical aspects and clinical utility of early fetal echocardiography and screening of the fetal heart in early pregnancy. Also, to document differences in cardiac structure and function which can be demonstrated in the late first/early second trimesters. METHODS: In addition to summarizing our own experiences of late first/early second trimester fetal echocardiography, we reviewed the literature to explore clinical indications for, technical aspects, safety, accuracy, strengths and weaknesses of early fetal echocardiography. RESULTS: In the current era, an increasing number of fetuses are identified as being at risk of congenital heart disease from as early as the late first trimester. In experienced hands, early fetal echocardiography can pick up a high proportion of congenital heart disease with good reliability for the majority of lesions. Early fetal echocardiography is relatively poor at assessing pulmonary veins, the atrioventricular valves and lesions that typically occur later or progress during the course of pregnancy. There is increasing interest in widespread implementation of an early obstetric anomaly screen which includes an assessment of the fetal heart for all pregnancies. There are a variety of hemodynamic differences in the late first/early second trimester compared with later in pregnancy. CONCLUSION: Early fetal echocardiography is has become an established tool for detection of congenital heart disease. It affords opportunities to learn about the true spectrum and progression of congenital heart disease in-utero. Operators should be mindful of safety issues, technical aspects and hemodynamic findings which differ when performing echocardiograms at this stage of pregnancy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".