Pulmonary artery/aorta ratio in simple screening for fetal outflow tract abnormalities during the second trimester
Bibliographic record
Abstract
OBJECTIVES: Congenital heart disease is associated with high mortality and morbidity rates, being the most life-threatening defect in the first month of postnatal life and accounting for approximately half of all childhood mortality from birth defects. Despite this, the prenatal detection rate for congenital outflow tract anomalies by ultrasound imaging is relatively low. The aim of this study was to establish a nomogram for the pulmonary artery/aorta (PA/AO) ratio measured in the three-vessel view plane. This ratio was investigated as a simple screening tool for congenital cardiac outflow tract abnormalities. METHODS: The study was a prospective evaluation of 966 singleton fetuses at 16-24 weeks of gestation and 46 fetuses with congenital cardiac outflow tract abnormalities. The diameters of the pulmonary artery and aorta were measured in the three-vessel view. The PA/AO ratio was calculated and a nomogram was constructed. The mean and 95% CI for the ratio were defined and the PA/AO ratios of cases with outflow tract abnormalities were plotted against the values for normal fetuses. RESULTS: The gestational age of the normal group ranged from 16 to 24 weeks, with a median of 19 weeks. The pulmonary artery diameter measured between 2.1 and 4.93 mm (mean, 3.3 mm) and the aorta measured between 2.1 and 5.2 mm (mean, 2.93 mm). The mean (SD) PA/AO ratio was 1.16 (0.18) (95% CI, 0.87-1.58; range 0.61-1.86; median, 1.14). For fetuses with outflow tract abnormalities, the median gestation was 19 weeks and 37/43 (86%) had a PA/AO ratio outside the 95% CI. CONCLUSIONS: The PA/AO ratio derived from measurements in the three-vessel view plane can be used as an initial screening tool for outflow tract anomalies and may have a sensitivity of up to 86%, with a 5% false-positive rate.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".