Prenatal assessment of congenital diaphragmatic hernia at north american fetal therapy network centers: A continued plea for standardization
Bibliographic record
Abstract
INTRODUCTION: Prenatal work-up for congenital diaphragmatic hernia (CDH) is important for risk stratification, standardization, counseling, and optimal therapeutic choice. To determine current practice patterns regarding prenatal CDH work-up, including prenatal ultrasound and magnetic resonance imaging (MRI) use, and to identify areas for standardization of such evaluation between fetal centers. METHODS: A survey regarding prenatal CDH work-up was sent to each member center of the North American Fetal Therapy Network (NAFTNet) (n = 36). RESULTS: All responded. Sonographic measurement of lung-to-head ratio (LHR) was determined by all, 89% (32/36) of which routinely calculate observed-to-expected LHR. The method for measuring LHR varied: 58% (21/36) used a "trace" method, 25% (9/36) used "longest axis," and 17% (6/36) used an "antero-posterior" method. Fetal MRI was routinely used in 78% (28/36) of centers, but there was significant variability in fetal lung volume measurement. Whereas all generated a total fetal lung volume, the planes, methodology and references values varied significantly. All evaluated liver position, 71% (20/28) evaluated stomach position and 54% (15/28) quantified the degree of liver herniation. More consistency in workup was seen between centers offering fetal intervention. CONCLUSION: Prenatal CDH work-up and management differs considerably among North American fetal diagnostic centers, highlighting a need for its standardization.
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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 | 0.027 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".