Development of <i>Z</i>‐scores for fetal cardiac dimensions from echocardiography
Bibliographic record
Abstract
OBJECTIVES: Z-scores for cardiac dimensions are well established in postnatal life, but have yet to be developed for fetal cardiac dimensions. These would be of real advantage to the clinician in accurately quantifying size and growth of cardiac dimensions and to the researcher by allowing mathematical comparison of growth in differing subgroups of a disease. The purpose of this observational study, conducted at tertiary fetal medicine and cardiology units, was to produce formulae and nomograms allowing computation of Z-scores for fetal cardiac dimensions from knowledge of femur length (FL), biparietal diameter (BPD) or gestational age (GA) using fetal echocardiography. METHODS: Seventeen fetal cardiac dimensions were measured in 130 pregnant women with singleton fetuses of gestational age 15-39 weeks. Regression equations were derived relating all dimensions to FL, BPD and GA. From the calculations, formulae were then developed allowing fetal cardiac Z-score computation. RESULTS: The relationships between cardiac dimensions and FL, BPD or GA were described following natural log transformation. From this analysis, FL (taken as an expression of fetal size) had the highest correlation to fetal cardiac dimensions. From the developed nomograms, Z-scores of specific fetal cardiac structures could be estimated from knowledge of the FL, BPD or GA and echocardiographically derived measurements. CONCLUSIONS: This study allowed computation of Z-scores in fetal life for 17 cardiac dimensions from FL, BPD or GA. Previous studies of normal data allowed qualitative assessment of where abnormal cardiac dimensions lay with regard to the normal range. Z-scores from this study allow quantitative analysis of where such dimensions lie relative to the mean. This permits exact assessment of growth of fetal cardiac structures in normal hearts and particularly in congenitally abnormal hearts where quantitative assessment of the growth of cardiac structures is important in analyzing and planning treatment strategies.
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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 | 0.009 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".