OP20.11: Contribution of morphologic and biometric markers to detection of 22 congenital heart defects (<scp>CHDs</scp>) by transvaginal sonography at 9–14 weeks of gestation
Bibliographic record
Abstract
Assess the relative values of morphologic and biometric markers in diagnosis of the 22 most common congenital heart defects (CHDs) detectable by 14 weeks of gestation. We utilised a multicentre database augmented with cases from the literature and analysed the occurrence of Very Frequent (VF) and Frequent (F) morphologic and biometric markers in the 22 CHDs, which fell into three classes of ultrasound-based natural history: Class I: anomalies with early onset at constant GA; Class II: potentially transients anomalies; Class III: anomalies with variable onset. Total 48 VF and F markers fulfilled the diagnostic requirements for the 22 CHDs, with 25 (52%) morphologic and 23 (48%) biometric (see table 1). Of the morphologic markers 20/25 (80%) were in Class I and 5/25 (20%) in Class II-III lesions, while of the biometric markers 7/23 (30%) were in Class I and 16/23 (70%) in Class II-III lesions at 14 wks. The incidence of Class II-III biometric markers in early pregnancy did not follow a horizontal rule across all the cases. Instead it varied according to the type and severity of morphologic markers per CHD. 48 sonomarkers cover the diagnostic requirements of the 22 most common types of CHDs by 14 wks. The scanning priority should be on C-I morphologic markers which are easier to detect at routine OB sonogram in early pregnancy than biometric markers, except deviations evident by “eyeball”. Severe morphologic markers in early pregnancy often flag the presence of associated biometric markers. Positive C-I and C-III markers have high diagnostic value in early pregnancy, while negative C-IIIs require rescanning at 18–22 wks. Markers of CHDs (15/22)
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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 | 0.001 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".