Diagnosis of congenital heart disease in an era of universal prenatal ultrasound screening in southwest Ohio
Bibliographic record
Abstract
OBJECTIVES: Diagnostic ultrasound is widespread in obstetric practice, yet many babies with major congenital heart disease remain undiagnosed. Factors affecting prenatal diagnosis of major congenital heart disease are not well understood. This study aims to document prenatal detection rates for major congenital heart disease in the Greater Cincinnati area, and identify factors associated with lack of prenatal diagnosis. METHODS: All living infants diagnosed with major congenital heart disease by 4 months of age at our centre were prospectively identified. Prenatal care data were obtained by parent interview. Neonatal records were reviewed for postnatal data. Obstetricians were contacted for diagnostic ultrasound data. RESULTS: A total of 100 infants met the inclusion criteria. In all, 95 infants were analysed, of whom 94 were offered diagnostic ultrasound. In all, 41 had a prenatal diagnosis of major congenital heart disease. The rate of prenatal detection varied by cardiac lesion, with aortic arch abnormalities, semilunar valve abnormalities, and venous anomalies going undetected in this sample. Among subjects without prenatal detection, the highest proportion consisted of those having Level 1 diagnostic ultrasound only (66%). Prenatal detection was not significantly influenced by maternal race, education level, income, or insurance type. CONCLUSIONS: Despite nearly universal diagnostic ultrasound, detection rates of major congenital heart disease remain low in southwest Ohio. An educational outreach programme including outflow tract sweeps for community-level obstetrical personnel may improve detection rates.
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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) | 0.001 | 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".