First-Trimester Prediction of Birth Weight
Bibliographic record
Abstract
OBJECTIVES: To determine whether the parameters used in first-trimester screening for aneuploidies contribute significantly to the prediction of birth weight. METHODS: In this retrospective cohort study (n = 4110), nuchal translucency (NT), free β-chorionic gonadotropin (fβ-hCG), and pregnancy-associated plasma protein-A (PAPP-A) blood concentrations were measured between 11 + 0 and 13 + 6 weeks. Multiple pregnancies, chromosomal anomalies, major fetal defects, and deliveries before 24 weeks were excluded. RESULTS: NT (0.95 versus 0.98 multiples of the expected median [MoM], p < 0.001) and PAPP-A (0.93 versus 1.06 MoM, p = 0.005) were significantly lower in small-for-gestational-age (SGA) newborns (<10th percentile) than the unaffected group, but not fβ-hCG (0.89 versus 0.93 MoM, p = 0.113). NT was significantly higher (1.03 versus 0.98 MoM, p < 0.001) in the large-for-gestational-age (LGA) group (>90th percentile) compared with the unaffected group, and biomarkers did not differ. After controlling for gestational age, maternal weight, smoking status, ethnicity, and fetal sex, first-trimester markers contributed to the prediction of birth weight in a multiple linear model but did not significantly improved the prediction of SGA and LGA compared with maternal characteristics alone. CONCLUSIONS: Parameters used in first-trimester screening for aneuploidies contribute to the prediction of birth weight but their clinical utility to detect women at risk of SGA or LGA baby is limited.
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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) | 0.000 | 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".